CN117332544A - Urban rainfall flood model modeling method by combining vector and grid hydrologic calculation unit - Google Patents
Urban rainfall flood model modeling method by combining vector and grid hydrologic calculation unit Download PDFInfo
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Abstract
The invention relates to a modeling method of a city rain and flood model by combining vectors with a grid hydrologic calculation unit, which comprises the following steps: the method comprises the steps of correcting a high-precision DEM by considering local topographic features of a geographic object, and modeling a grid hydrologic calculation unit by combining hydrologic parameters; according to the space topology and the connection relation of the drainage pipe network, carrying out drainage pipe network modeling; simulating according to typical rainfall occasions, and extracting a simulated result rainfall flood situation; dividing an urban catchment area according to the converging situation characteristics of the simulation result, and constructing a vector grid collaborative hydrologic calculation unit boundary; and estimating characteristic parameters of the vector hydrologic calculation unit by using submerged situation characteristics and converging situation characteristics of the grid simulation result, and performing rating optimization on the parameters to complete construction of the vector grid collaborative urban rainfall flood model. The invention is beneficial to improving the modeling quality and the simulation efficiency of the urban rainfall flood model, expands the modeling and the simulation methods of the existing urban rainfall flood model, and expands the application of GIS in urban hydrology and natural disaster management.
Description
Technical Field
The application relates to the field of geographic information system technology and urban hydrology, in particular to a modeling method of an urban rainfall flood model by combining vectors with grid hydrologic calculation units.
Background
In order to effectively cope with waterlogging disasters and their adverse effects, more and more measures are being implemented in the field in waterlogging disaster management. The urban rainfall flood model auxiliary decision analysis is an effective non-engineering measure and is widely applied to urban rainfall flood disaster analysis, prediction and disaster response scheduling.
The urban rainfall flood model is mainly based on distributed simulation, the distributed simulation disperses the earth surface space into a series of hydrologic calculation units, and a hydrodynamic or hydrologic formula is adopted to simulate the rainwater flowing process inside the units and among the units. Urban rainfall flood models can be divided into hydrodynamic models and hydrologic models according to the discrete manner of the surface space. The hydrodynamic model disperses the surface space into a series of grid units reflecting the elevation, and a hydrodynamic equation is adopted to simulate the flow of rainwater under the action of gravity on the grid units. The hydrologic model discretizes the earth's surface into a series of vector planes that generally characterize the drainage basin or catchment area, and the model employs conceptual hydrologic equations to abstract the rainfall production and convergence process within the expression vector planes. Although both the hydrodynamic model and the hydrologic model are suitable for urban rainfall flood simulation, the two are obviously different in simulation accuracy, operation efficiency and expression capability for rainfall flood situations. Existing urban flood simulations mostly consider only one of the models or simply couple the two models in series. The simulation method does not take the advantages and features of the two models into consideration well, and the two models are not combined from the level of the bottom hydrologic calculation unit, so that the simulation performance is improved.
In summary, there is currently no efficient and accurate modeling method for urban rainfall flood model by combining vectors with grid hydrologic calculation units.
Disclosure of Invention
Aiming at the defects of the existing urban rainfall flood model modeling method, the method for modeling the urban rainfall flood model by combining vectors with grid hydrologic calculation units is provided, from the information geography perspective, the data structure and the operation mechanism of the hydrologic model and the hydrologic model bottom layer hydrologic calculation units are deeply analyzed, the spatial characteristics and the hydrologic attribute characteristics of the two are compared, and the method for collaborative modeling and collaborative simulation of the two hydrologic calculation units is provided, so that the two models can complement each other, and the simulation of the urban rainfall flood process is completed in a collaborative and consistent manner, and the modeling quality and the simulation efficiency of the urban rainfall flood model are improved; the space-time analysis and space data organization management capability of the GIS are fully utilized, the modeling and simulation method of the existing urban rainfall flood model is expanded, and the application of the GIS in urban hydrology and natural disaster management is expanded.
The application provides a modeling method of a city rain and flood model by combining vectors with a grid hydrologic calculation unit, which comprises the following steps:
step S1: according to the high-precision DEM, grid hydrologic calculation unit modeling is carried out on the modeling area, the boundaries of the vector hydrologic calculation units are further divided by combining underground drainage pipe network data, characteristic parameters are calculated, parameter calibration is carried out, and urban rainfall flood model construction by cooperation of the grid and the vector hydrologic calculation units is realized;
step S2: according to the modeling area scale, carrying out resolution adjustment on the high-precision data DEM, carrying out special treatment on local topographic features, configuring hydrological parameters such as Manning roughness coefficient, infiltration rate, initial water depth and the like, and thus completing modeling of the grid hydrological calculation unit;
step S3: connecting a rainwater well with a drainage port by utilizing a rainwater pipeline, constructing a space topological relation and a space connection relation of the rainwater well, and performing data cleaning and generalization to complete modeling of an underground drainage pipe network;
step S4: extracting the grid converging flow direction of the earth surface, constructing a nuclear density matrix based on the combination of the distance similarity and the direction similarity of the rainwater wells, carrying out boundary division of a vector hydrologic calculation unit (namely a hydrologic calculation unit with the cooperation of the vector and the grid) of the grid converging flow direction constraint through a region growing algorithm considering the flow direction connectivity, and correcting the result;
step S5: the characteristic parameters of the vector hydrologic calculation unit such as the characteristic width of the catchment area, the gradient of the catchment area and the watertight area ratio are calculated in an auxiliary mode by using the simulation situations such as the submerged water depth, the flow direction, the flow rate and the flow velocity of the grid hydrologic calculation unit;
step S6: and calibrating parameters such as the Manning coefficient of the permeable/impermeable surface, the water storage capacity of the permeable/impermeable surface depressions, the water storage surface proportion of the impermeable non-depression surface and the like, including characteristic parameters, by utilizing a genetic algorithm, and completing the construction of the urban rainfall flood model by the cooperation of the grid and the vector hydrologic calculation unit.
Furthermore, as urban earth surface modeling of the grid hydrologic simulation unit mainly depends on DEM data, the urban earth surface modeling has certain requirements on the spatial resolution of the DEM, and special treatment is required to be carried out on certain geographic objects and local topographic features; meanwhile, the grid hydrologic calculation unit reflects the rainwater converging process through flow exchange among the units, and the related partial hydrologic parameters are assigned according to actual conditions.
Therefore, the step S2 includes the steps of:
step S21: for city scale, the model usually adopts DEM with resolution of 5m and above as input, which is limited by operation efficiency; for the block scale, a DEM with a resolution of 1m to 5m is adopted;
step S22: the local topographic features are specially treated by two treatment methods: firstly, carrying out detail treatment on a building roof by utilizing fine topographic data, and collecting rainwater pipe network elements of the roof for modeling; secondly, neglecting the yield of the roof of the building and generalizing the yield;
step S23: and assigning parameters such as a Man Ning Caolv coefficient, a infiltration rate, an initial water depth and the like according to the specific land utilization type.
Further, the vector hydrologic calculation unit is used to characterize a urban catchment area, which in urban areas usually refers to the catchment area of a catch basin, which area is usually tens to thousands of square meters. The hydrologic phenomenon contained in the space range is large in scale, and a series of hydrologic processes such as rainfall, runoff generation, confluence, rainwater well overflow and the like are covered. Therefore, modeling of the underground drainage network is required based on the rainwater network data.
Therefore, the step S3 includes the steps of:
step S31: according to the space parameters of the rainwater well and the rainwater pipeline, connecting the rainwater well with the drainage port by utilizing the rainwater pipeline, constructing a space topological relation and a space connection relation of the rainwater well and the drainage port, and establishing a net structure taking the drainage port as a terminal point;
step S32: the method comprises the steps of cleaning pipe network data, including removing detection points and sewage nodes, and checking pipe network connectivity;
step S33: and carrying out data summarization on pipe network data, extracting main rainwater well nodes, removing branch nodes which are closer to the main rainwater well nodes, and properly expanding the cross-sectional area of the main rainwater well nodes.
Furthermore, the hydrologic process of the grid hydrologic simulation unit is simple, and only the flow can be generated from the X-axis direction or the Y-axis direction, so that the superposition analysis is carried out on the X-axis flow direction grid and the Y-axis flow direction grid according to the D8 flow direction algorithm, and the surface flow direction grid is extracted; based on the principle that the traditional catchment area division is gradually refined from large to small, the distance similarity and the direction similarity of a rainwater well and grid units are combined, a region growing algorithm considering flow direction connectivity is designed to conduct the boundary division of a vector hydrologic calculation unit (namely a hydrologic calculation unit with the cooperation of vectors and grids) for grid converging flow direction constraint, and the division result is corrected.
Therefore, the step S4 includes the steps of:
step S41: according to a D8 flow direction algorithm, performing superposition analysis on the X-axial flow direction grid and the Y-axial flow direction grid, and converting the X-axial flow direction grid and the Y-axial flow direction grid into a flow direction grid represented by a D8 flow direction code;
step S42: the Euclidean distance is used for calculating the distance similarity between the grid unit and the rainwater well, and the smaller the Euclidean distance between two points is, the larger the distance similarity is; the Euclidean distance is converted into the distance similarity by adopting a normalization method, and the calculation formula is as follows:
，
，
in the method, in the process of the invention,、/>is +.>Coordinate sum->Coordinates; />、/>Is +.>Coordinate sum->Coordinates; />Is the Euclidean distance between two points; />The similarity of the distance between two points;
step S43: calculating the direction similarity of the grid flow direction and the direction of the connecting line of the grid and the rainwater well according to a cosine similarity formula, wherein when the included angle of the vector line is 0 degree and the direction is completely consistent, the cosine value is 1, and for any other angle, the cosine value is smaller than 1; after normalization, the calculation formula of the direction similarity is as follows:
，
in the method, in the process of the invention,the unit is radian for the included angle of the vector; />Is the similarity of the directions;
step S44: the joint distance similarity and the direction similarity construct joint similarity, and the calculation formula of the joint similarity is as follows:
，
in the method, in the process of the invention,for joint similarity, ++>Distance similarity>For the similarity of directions, add>Is the regulation coefficient of distance similarity, +.>Is a regulation coefficient of the direction similarity;
step S45: the nuclear density estimation is carried out on the rainwater well data to generate a regional nuclear density matrix, and the nuclear density is introduced into the joint similarity, and the expression is as follows:
，
in the method, in the process of the invention,normalized nuclear density value for grid cell, +.>Distance similarity>For the similarity of directions, add>Is joint similarity;
step S46: according to a region growing algorithm, combining a kernel density matrix, comprehensively considering flow direction connectivity among grids, and dividing boundaries of a vector hydrologic calculation unit;
step S47: the rainwater well catchment area divided by the area growth algorithm is not completely accurate, and a mode filter is needed to be used for correction processing, so that a final vector and grid collaborative hydrologic calculation unit is obtained.
Furthermore, after the division of the vector and grid collaborative hydrologic calculation unit is completed, the characteristic parameters of the vector and grid collaborative hydrologic calculation unit are calculated to be used for urban rainfall flood simulation. The characteristic parameters include parameters characterizing the spatial characteristics of the catchment area, such as characteristic width, average slope, and water-impermeable area ratio. The parameters reflect the spatial characteristics of the internal confluence of the catchment area, the value of the parameters is relatively fixed, and the parameters are not influenced by external conditions such as rainfall situations, seasons, temperature, humidity and the like; at the same time, these parameters can be determined directly from the simulated situation of the grid (flow field, water depth, flooding range).
Therefore, the step S5 includes the steps of:
step S51: introducing a flow-diffusing length concept, calculating a maximum converging path, a converging area and a flow-diffusing length through the flow direction of the grid hydrologic calculation unit, and quantifying the characteristic width of the catchment area;
step S52: according to the ground elevation fluctuation and the maximum converging path, calculating the descending gradient of the catchment area, namely the gradient of the catchment area;
step S53: and carrying out superposition analysis on the land utilization type data and the catchment area units, or calculating the water-impermeable area ratio of the catchment area by counting the ratio of the number of grid hydrologic calculation units without infiltration rate in the catchment area units to the total number of units.
Further, the feature parameters and the remaining hydrologic parameters need to be further optimized and calibrated to improve the accuracy of the simulation result. The genetic algorithm is an algorithm for searching an optimal solution set by simulating a natural selection and evolution process, is commonly used for parameter optimization, and can take an evaluation index obtained by calculating a simulation value and target data of a hydrologic calculation unit as an fitness function in individuals of a genetic algorithm population, so that parameter updating iteration of the hydrologic calculation unit with vector and grid cooperation is completed.
Therefore, the step S6 includes the steps of:
step S61: before parameter calibration, the value range of the vector hydrologic calculation unit parameter is required to be determined and a parameter initial value is given;
step S62: and carrying out parameter calibration on the vector hydrologic calculation unit by adopting a genetic algorithm, so that the inlet flow of each rainwater well of the vector hydrologic calculation unit can be similar to that of the grid hydrologic calculation unit, and the consistency of the outlet flow of the vector hydrologic calculation unit and the grid hydrologic calculation unit at the discharge port is verified.
Compared with the prior art, the advantage and beneficial effect of this application lie in:
(1) The proposal explores hydrologic calculation units of a hydrologic rainfall flood model and a hydrodynamic rainfall flood model from the view of information geography, analyzes the characteristics of a spatial data structure, digs the spatial characteristics formed by the spatial data structure under the constraint of a specific spatial data structure and the expression mode of the urban rainfall flood process,
(2) The proposal analysis compares the space characteristics and the hydrologic attribute characteristics of the hydrologic model and the hydrologic model bottom hydrologic calculation unit, proposes the cooperative modeling and the cooperative simulation method of the two hydrologic calculation units, so that the two models can complement each other, the urban rainfall flood process simulation can be completed in a cooperative and consistent way, the modeling quality and the simulation efficiency of the urban rainfall flood model are improved,
(3) The scheme utilizes the GIS theory technology to promote the organic fusion of the hydrodynamic model and the hydrologic model on the hydrologic calculation unit level, expands the modeling and simulation method of the existing urban rainfall flood model, expands the application of the GIS in the aspects of urban hydrologic and natural disaster management, and is the practice and innovation of the GIS in the modeling and simulation of the geographic process.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will make brief description of the drawings used in the description of the embodiments or the prior art.
FIG. 1 is a flowchart of a modeling method of an urban rainfall flood model with a vector and grid hydrologic calculation unit in cooperation, provided in an embodiment of the present application;
FIG. 2 is a block diagram of a specific application of a modeling method of urban rainfall flood model with cooperation of vectors and grid hydrologic calculation units according to the embodiment of the present application;
FIG. 3 is a graph showing the results of modeling area digital elevation model corrections provided in an embodiment of the present application;
FIG. 4 is a graph showing the results of modeling area underground drainage network treatment provided in an embodiment of the present application;
FIG. 5 is a simulation result of a surface water depth in a rain fall using a hydrologic model for a modeling area provided by an example of the present application;
FIG. 6 is a modeling area surface water flow simulation result provided by an embodiment of the present application;
FIG. 7 is a graph showing the results of a modeling area rain well core density analysis provided in an embodiment of the present application;
FIG. 8 is a graph showing the result of the division of the hydrologic calculation units of the vector and grid cooperation provided in the embodiment of the present application;
FIG. 9 is a flowchart of a genetic algorithm provided in an embodiment of the present application;
FIG. 10 is a flow chart of parameter calibration and verification provided in an embodiment of the present application;
figure 11 is a simulated graph of the outfall1 flow in the embodiment of the present application,
figure 12 is an example of an outfall2 flow simulation,
figure 13 is an exemplary outfall3 flow simulation curve of the present application,
fig. 14 is an outfall4 flow simulation curve in the embodiment of the present application.
Detailed Description
Embodiments of the technical solutions of the present application will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical solutions of the present application, and are therefore only examples, and are not intended to limit the scope of protection of the present application. It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this application belongs. The present application will be described in further detail with reference to the accompanying drawings and examples.
Examples: a modeling method of a city rain and flood model by combining vectors with grid hydrologic calculation units comprises the following steps:
according to the embodiment shown in fig. 1, the present application provides a modeling method for urban rainfall flood model by combining vectors with grid hydrologic calculation units, which specifically comprises the following steps:
a modeling method of a city rain and flood model by combining vectors with grid hydrologic calculation units is characterized by comprising the following steps:
step S1: according to the high-precision DEM, grid hydrologic calculation unit modeling is carried out on the modeling area, the boundaries of the vector hydrologic calculation units are further divided by combining underground drainage pipe network data, characteristic parameters are calculated, parameter calibration is carried out, and construction of a city rainfall flood model with cooperation of the vector and the grid hydrologic calculation units is realized;
step S2: according to the modeling area scale, carrying out resolution adjustment on the high-precision data DEM, carrying out special treatment on local topographic features, configuring hydrological parameters such as Manning roughness coefficient, infiltration rate, initial water depth and the like, and thus completing modeling of the grid hydrological calculation unit;
step S3: connecting a rainwater well with a drainage port by utilizing a rainwater pipeline, constructing a space topological relation and a space connection relation of the rainwater well, and performing data cleaning and generalization to complete modeling of an underground drainage pipe network;
step S4: extracting the grid converging flow direction of the earth surface, constructing a nuclear density matrix based on the combination of the distance similarity and the direction similarity of the rainwater wells, dividing the boundaries of vector hydrologic calculation units (namely, hydrologic calculation units with the cooperation of vectors and grids) with the constraint of the grid converging flow direction by a region growing algorithm considering the connectivity of the flow direction, and correcting the division result;
step S5: the characteristic parameters of the vector hydrologic calculation unit such as the characteristic width of the catchment area, the gradient of the catchment area and the watertight area ratio are calculated in an auxiliary mode by using the simulation situations such as the submerged water depth, the flow direction, the flow rate and the flow velocity of the grid hydrologic calculation unit;
step S6: and calibrating parameters such as the Manning coefficient of the permeable/impermeable surface, the water storage capacity of the permeable/impermeable surface depressions, the water storage surface proportion of the impermeable non-depression surface and the like, including characteristic parameters, by utilizing a genetic algorithm, and completing the construction of the urban rainfall flood model by the cooperation of the grid and the vector hydrologic calculation unit.
In this embodiment, modeling of the urban rainfall flood model of a certain community (11 ha) is completed by using DEM data, basic geographic data, land utilization/coverage data and rainwater pipe network data of the certain community.
The implementation steps are as shown in fig. 2:
step one: and (3) carrying out resolution adjustment on the high-precision data DEM according to the dimension of the modeling area, carrying out special treatment on local topographic features, and configuring hydrological parameters such as Manning roughness coefficient, infiltration rate, initial water depth and the like, so as to complete modeling of the grid hydrological calculation unit. The detailed steps are as follows:
step (1): because the modeling area is a city community, the scale is small and the data fineness is high, the terrain is expressed by selecting 1 m-precision DEM, and the number of grids is；
Step (2): the integral topography of the area is higher in the west and north, lower in the east and south and surrounded by the river, so that the DEM of the river area is corrected, and the initial water depth is set to be 1m according to the actual water level of the river;
step (3): the elevation point of the building coverage area in the area is inaccurate, the building range can be seen according to the DEM, but the actual topography of the building roof cannot be clearly reflected, so that the grid units of the building are removed, and the corrected DEM data are shown in fig. 3.
Step two: and connecting the rainwater well with the drainage port by utilizing a rainwater pipeline in the modeling area, constructing a spatial topological relation and a spatial connection relation of the rainwater well and the drainage port, cleaning and generalizing data, and finishing modeling of the underground drainage pipe network. The detailed steps are as follows:
step (1): analyzing the space connection relation according to attribute fields of the vector data of the rainwater pipeline, the rainwater well and the drainage port, and connecting the three according to the topological relation;
step (2): the rainwater pipe network data in the area are analyzed, and the data contains a large number of detection wells, sewage wells and isolated rainwater well nodes. Traversing the nodes by designing a breadth-first algorithm, marking the nodes which are not traversed as isolated nodes, and deleting 2048 isolated nodes, bilge well nodes and inspection well nodes according to the data marks;
step (3): after data cleaning, 1240 dewatering well nodes, 1242 drainage lines and 5 drainage port nodes are still stored in the research area. Because the pipeline data of the pipeline points are too dense, the rest rainwater pipeline network is generalized by adopting a generalization method, and finally 337 rainwater well nodes, 337 drainage pipelines and 5 drainage port nodes are remained, and the pipeline network processing result is shown in figure 4.
Step three: and extracting a grid converging flow direction of the ground surface of the modeling area, constructing a nuclear density matrix based on the combination of the distance similarity and the direction similarity of the rainwater well, and carrying out the boundary division of the grid converging flow direction constraint vector hydrologic calculation unit, namely the hydrologic calculation unit with the cooperation of the vector and the grid by an area growth algorithm considering the flow direction connectivity, and correcting the result. The detailed steps are as follows:
step (1): after the grid hydrologic calculation unit and the underground drainage pipe network are modeled, rainfall is adopted for 50 years after 3 hours as input data of a hydrologic model to simulate rainfall flood, the simulation duration is set to be 5 hours, and the simulation water depth is shown in fig. 5;
step (2): through statistics, the water accumulation depth of the earth surface is mainly concentrated between 0 and 0.3m at the moment when the average water depth of the grid is maximum in 1 hour 40, and the water accumulation in a large range is generated in the middle area of the research area due to the small distribution quantity of pipe networks. Extracting the flow direction result of 40-minute grid simulation at 1 time, and encoding the flow direction result by adopting a D8 encoding format, wherein the local overall flow direction trend can be found to be from west to east and from north to south, as shown in fig. 6;
step (3): and calculating the distance similarity between the grid unit and the rainwater well by using the Euclidean distance. The closer the grid unit is to the catch basin, the higher the distance similarity between the two is, and the greater the possibility that the grid unit is integrated into the catch basin catchment area of the catch basin is, namely the smaller the Euclidean distance between the two points is, the greater the distance similarity is; the Euclidean distance is converted into the distance similarity by adopting a normalization method, and the calculation formula is as follows:
，
，
in the method, in the process of the invention,、/>is +.>Coordinate sum->Coordinates; />、/>Is +.>Coordinate sum->Coordinates; />Is the Euclidean distance between two points; />The similarity of the distance between two points;
step (4): and calculating the grid flow direction and the similarity of the grid and the direction of the connecting line of the rainwater well. The water flow direction around the catch basin is more likely to sink into the catch basin if it is directed towards the catch basin. The directional similarity measures the cosine value of the two vector clamp angles, and the cosine value range is between-1 and 1. When the included angle of the vector lines is 0 degree and the directions are completely consistent, the cosine value is 1, and for any other angle, the cosine value is less than 1. After normalization, the calculation formula of the direction similarity is as follows:
，
in the method, in the process of the invention,the unit is radian for the included angle of the vector; />Is the similarity of the directions;
step (5): the joint distance similarity and the direction similarity are required to construct the joint similarity. The calculation formula of the joint similarity is as follows:
，
in the method, in the process of the invention,for joint similarity, ++>Distance similarity>For the similarity of directions, add>Is the regulation coefficient of distance similarity, +.>Is a regulation coefficient of the direction similarity;
step (6): the nuclear density estimation of the catch basin data can generate a regional nuclear density matrix, and the regional catch basin nuclear density analysis result is shown in fig. 7. In order to facilitate calculation, the nuclear density matrix needs to be normalized, so that the value range of the nuclear density matrix is between 0 and 1, and the normalized nuclear density is introduced into the joint similarity, and the expression is as follows:
，
in the method, in the process of the invention,normalized nuclear density value for grid cell, +.>Distance similarity>For the similarity of directions, add>Is joint similarity; after the nuclear density of the rainwater wells is used as a regulating and controlling coefficient to be introduced into a joint similarity calculation formula, the weight of the distance similarity in a rainwater well dense region is reduced, the weight in a rainwater well sparse region is increased, and the direction similarity is opposite;
step (7): according to the method, a rainwater well nuclear density matrix and a grid flow direction simulation result are combined, grid units where rainwater well nodes are located are used as seed points, and a region growing algorithm considering flow direction connectivity is adopted to carry out diffusion division on a water collecting region of the rainwater well;
step (8): the rainwater well catchment area divided by the area growth algorithm is not completely accurate, a plurality of tiny fragments exist between the catchment areas, and the fragments are undefined areas and need to be treated by a mode filter; the final division result is shown in fig. 8, and each vector hydrologic calculation unit corresponds to one rainwater well node, and 337 vector hydrologic calculation units are drawn in total.
Step four: and the characteristic parameters of the vector hydrologic calculation unit such as the characteristic width of the catchment area, the gradient of the catchment area and the watertight area ratio are calculated in an auxiliary mode by using the simulation situations such as the submerged water depth, the flow direction, the flow rate and the like of the grid hydrologic calculation unit. The detailed steps are as follows:
step (1): according to the flow direction simulation result of the grid hydrologic calculation unit, counting the confluence accumulation amount of the grids in each vector grid cooperative hydrologic calculation unit, and connecting the grids with the largest confluence accumulation amount to obtain a maximum confluence path, wherein the length of the path can represent the total confluence length of the vector hydrologic calculation unit;
step (2): dividing the maximum confluence path length by the unit area to obtain a characteristic width; dividing the height difference of the maximum converging path by the length of the maximum converging path to obtain a characteristic gradient; and calculating the ratio of vegetation coverage to bare land in each unit to obtain the water-impermeable area ratio.
Step five: and calibrating parameters such as the Manning coefficient of the permeable/impermeable surface, the water storage capacity of the permeable/impermeable surface depressions, the water storage surface proportion of the impermeable non-depression surface and the like, including characteristic parameters, by utilizing a genetic algorithm, and completing the construction of the urban rainfall flood model by the cooperation of the grid and the vector hydrologic calculation unit. The detailed steps are as follows:
step (1): before parameter calibration is carried out by using a genetic algorithm, the value range of the parameter is required to be determined and an initial value of the parameter is given; the assignment of the parameters of the vector hydrologic calculation unit corresponding to a certain catch basin is shown in the following table: parameter assignment table for water-rain well
Step (2): ensuring vector hydrologyThe rainfall input of the calculation unit is consistent with that of the grid hydrologic calculation unit, the rainfall input grid hydrologic calculation unit is simulated to obtain the input flow simulation result of each rainwater well, and a calibration data set is formed；
Step (3): based on the calibration data set, carrying out parameter calibration on the vector hydrologic calculation unit by adopting a genetic algorithm, so that the inflow rate of each rainwater well of the vector hydrologic calculation unit can be similar to that of the grid hydrologic calculation unit, and the genetic algorithm flow and parameter calibration and verification are shown in fig. 9 and 10;
step (4): after parameter calibration, the Nash efficiency coefficient (NSE) of the flow curve of the vector hydrologic calculation unit and the grid hydrologic calculation unit at the main discharge port is more than 0.90, the Pearson Correlation Coefficient (PCCs) is more than 0.95, and as shown in fig. 11-14, the simulation result of the modeling method of the urban rainfall flood model by the cooperation of the vector and the grid hydrologic calculation unit provided by the embodiment of the application is compared with the simulation result of the grid hydrologic calculation unit, wherein fig. 11 is an outfall1 flow simulation curve, fig. 12 is an outfall2 flow simulation curve, fig. 13 is an outfall3 flow simulation curve, and fig. 14 is an outfall4 flow simulation curve.
The method shows that the two hydrologic calculation units are cooperated, and the construction of the urban rainfall flood model with the cooperation of the vector and the grid hydrologic calculation units is completed.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the embodiments, and are intended to be included within the scope of the claims and description.
Claims (6)
1. A modeling method of a city rain and flood model by combining vectors with grid hydrologic calculation units is characterized by comprising the following steps:
step S1: according to the high-precision DEM, grid hydrologic calculation unit modeling is carried out on the modeling area, the boundaries of the vector hydrologic calculation units are further divided by combining underground drainage pipe network data, characteristic parameters are calculated, parameter calibration is carried out, and urban rainfall flood model construction by cooperation of the grid and the vector hydrologic calculation units is realized;
step S2: according to the modeling area scale, carrying out resolution adjustment on the high-precision data DEM, carrying out special treatment on local topographic features, and configuring Manning roughness coefficients, infiltration rate and initial hydrographic parameters so as to complete modeling of the grid hydrographic calculation unit;
step S3: connecting a rainwater well with a drainage port by utilizing a rainwater pipeline, constructing a space topological relation and a space connection relation of the rainwater well, and performing data cleaning and generalization to complete modeling of an underground drainage pipe network;
step S4: extracting the grid converging flow direction of the earth surface, constructing a nuclear density matrix based on the combination of the distance similarity and the direction similarity of the rainwater wells, dividing the boundary of a vector hydrologic calculation unit which is used for restricting the grid converging flow direction by a region growing algorithm taking the connectivity of the flow direction into consideration, namely a hydrologic calculation unit which coordinates the vector and the grid, and correcting the division result;
step S5: the submerged water depth, flow direction, flow rate and flow speed simulation situation of the grid hydrologic calculation unit is utilized to assist in calculating characteristic parameters of the catchment area characteristic width, catchment area gradient and impermeable area ratio vector hydrologic calculation unit;
step S6: and calibrating the water permeable/impermeable surface Manning coefficient, the water permeable/impermeable surface depression water storage capacity and the water impermeable depression-free water storage surface proportion parameters including the characteristic parameters by utilizing a genetic algorithm, and completing the construction of the urban rainfall flood model by the cooperation of the grid and the vector hydrologic calculation unit.
2. The modeling method of urban rainfall flood model with vector and grid hydrologic calculation unit according to claim 1, wherein the step S2 comprises the following steps:
step S21: for city scale, the model adopts DEM with resolution of 5m and above as input due to operation efficiency; for the block scale, a DEM with a resolution of 1m to 5m is adopted;
step S22: the local topographic features are specially treated by two treatment methods: firstly, carrying out detail treatment on a building roof by utilizing fine topographic data, and collecting rainwater pipe network elements of the roof for modeling; secondly, neglecting the yield of the roof of the building and generalizing the yield;
step S23: and assigning the Man Ning Caolv coefficient, the infiltration rate and the initial water depth parameter according to the specific land utilization type.
3. The modeling method of urban rainfall flood model with vector and grid hydrologic calculation unit according to claim 1, wherein the step S3 comprises the following steps:
step S31: according to the space parameters of the rainwater well and the rainwater pipeline, connecting the rainwater well with the drainage port by utilizing the rainwater pipeline, constructing a space topological relation and a space connection relation of the rainwater well and the drainage port, and establishing a net structure taking the drainage port as a terminal point;
step S32: the method comprises the steps of cleaning pipe network data, including removing detection points and sewage nodes, and checking pipe network connectivity;
step S33: and carrying out data summarization on pipe network data, extracting main rainwater well nodes, removing branch nodes which are closer to the main rainwater well nodes, and properly expanding the cross-sectional area of the main rainwater well nodes.
4. The modeling method of urban rainfall flood model with vector and grid hydrologic calculation unit according to claim 1, wherein the step S4 comprises the following steps:
step S41: according to a D8 flow direction algorithm, performing superposition analysis on the X-axial flow direction grid and the Y-axial flow direction grid, and converting the X-axial flow direction grid and the Y-axial flow direction grid into a flow direction grid represented by a D8 flow direction code;
step S42: the Euclidean distance is used for calculating the distance similarity between the grid unit and the rainwater well, and the smaller the Euclidean distance between two points is, the larger the distance similarity is; the Euclidean distance is converted into the distance similarity by adopting a normalization method, and the calculation formula is as follows:
in the method, in the process of the invention,、/>is +.>Coordinate sum->Coordinates; />、/>Is +.>Coordinate sum->Coordinates;is the Euclidean distance between two points; />The similarity of the distance between two points;
step S43: calculating the direction similarity of the grid flow direction and the direction of the connecting line of the grid and the rainwater well according to a cosine similarity formula, wherein when the included angle of the vector line is 0 degree and the direction is completely consistent, the cosine value is 1, and for any other angle, the cosine value is smaller than 1; after normalization, the calculation formula of the direction similarity is as follows:
in the method, in the process of the invention,the unit is radian for the included angle of the vector; />Is the similarity of the directions;
step S44: the joint distance similarity and the direction similarity construct joint similarity, and the calculation formula of the joint similarity is as follows:
in the method, in the process of the invention,for joint similarity, ++>Distance similarity>For the similarity of directions, add>Is the regulation coefficient of distance similarity, +.>Is a regulation coefficient of the direction similarity;
step S45: the nuclear density estimation is carried out on the rainwater well data to generate a regional nuclear density matrix, and the nuclear density is introduced into the joint similarity, and the expression is as follows:
，
in the method, in the process of the invention,normalized nuclear density value for grid cell, +.>Distance similarity>For the similarity of directions, add>Is joint similarity;
step S46: according to a region growing algorithm, combining a kernel density matrix, comprehensively considering flow direction connectivity among grids, and dividing boundaries of a vector hydrologic calculation unit;
step S47: the rainwater well catchment area divided by the area growth algorithm is not completely accurate, and a mode filter is needed to be used for correction processing, so that a final vector hydrologic calculation unit is obtained.
5. The modeling method of urban rainfall flood model with vector and grid hydrologic calculation unit according to claim 1, wherein the step S5 comprises the following steps:
step S51: introducing a flow-diffusing length concept, calculating a maximum converging path, a converging area and a flow-diffusing length through the flow direction of the grid hydrologic calculation unit, and quantifying the characteristic width of the catchment area;
step S52: according to the ground elevation fluctuation and the maximum converging path, calculating the descending gradient of the catchment area, namely the gradient of the catchment area;
step S53: and carrying out superposition analysis on the land utilization type data and the catchment area units, or calculating the water-impermeable area ratio of the catchment area by counting the ratio of the number of grid hydrologic calculation units without infiltration rate in the catchment area units to the total number of units.
6. The modeling method of urban rainfall flood model with vector and grid hydrologic calculation unit according to claim 1, wherein the step S6 comprises the following steps:
step S61: before parameter calibration, the value range of the vector hydrologic calculation unit parameter is required to be determined and a parameter initial value is given;
step S62: and carrying out parameter calibration on the vector hydrologic calculation unit by adopting a genetic algorithm, so that the inlet flow of each rainwater well of the vector hydrologic calculation unit can be similar to that of the grid hydrologic calculation unit, and the consistency of the outlet flow of the vector hydrologic calculation unit and the grid hydrologic calculation unit at the discharge port is verified.
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