Sponge city runoff evaluation method and system

Abstract

The invention discloses a sponge city runoff evaluation method and system, and belongs to the technical field of runoff monitoring, and the method comprises the steps: processing image data obtained based on an unmanned plane oblique photography technology, and obtaining a DOM and a DEM of a sponge city research region; according to the DOM and the DEM, using ArcGIS software to divide sub catchment areas and extracting geometric parameter data of the sub catchment areas; obtaining infiltration parameter data required by the SWMM model based on the unmanned aerial vehicle oblique photography technology through a soil infiltration experiment; and inputting the geometric parameter data and the infiltration parameter data into the SWMM model, carrying out manual calibration on residual parameters of the SWMM model, adding rainfall data, constructing the SWMM model based on an unmanned aerial vehicle oblique photography technology, and evaluating a sponge city total runoff amount control target by simulating and researching a regional surface runoff process. According to the method, the evaluation accuracy of sponge city runoff simulation is improved, and the requirement for simulation of total runoff control of a single facility or a higher-precision model in sponge city construction can be met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of runoff monitoring, and more particularly to a method and system for digital simulation and evaluation of runoff of a sponge city based on tilt photography measurement technology of a UAV. BACKGROUND

[0002] Sponge city construction is a modern urban development concept. By strengthening urban planning, construction management, the city sponge body is protected and restored, and the rainwater runoff is effectively controlled, so as to realize the transformation from end treatment to source reduction, process control and system management. This transformation changes the city water treatment method from simple discharge to retention, infiltration, storage, purification, utilization and discharge, so as to achieve the purposes of repairing urban water ecology, improving urban water environment, guaranteeing urban water safety and improving urban water resource carrying capacity, so as to improve the quality of new urbanization. In order to better construct the sponge city, the control of runoff index is crucial. Runoff can measure whether the construction of a city or a region meets the requirements of a sponge city, clarify the existing problems and gaps, and provide effective guidance for the construction of a sponge city.

[0003] Since the research and construction of sponge cities in China are in the initial stage, the academic research on the evaluation index system mainly focuses on the significance and decomposition of the annual runoff control rate. The national standard "Sponge City Construction Evaluation Standard" GB / T51345-2018 lists the annual runoff control rate and runoff volume control as one of the necessary evaluation contents. At present, the evaluation methods for annual runoff control rate and runoff volume control mainly include monitoring method and simulation method. The monitoring method needs to invest monitoring equipment, usually requires more than one year of continuous monitoring, and has high cost and large demand for manual labor. The model simulation method mainly uses the data in the design scheme of the sponge city combined with the terrain rainfall data required by the model, and evaluates after generalization by the model, which meets the evaluation needs of multi-scale and multi-target, and saves manpower, material resources and financial resources. Although the model simulation method is a more optimal choice, the model simulation depends on the accuracy and timeliness of DEM and surface data, and the accuracy of the model is the core factor affecting the accuracy of the evaluation. At present, the resolution of open source satellite DEM data is 90m, 30m and 12.5m, and the precision of domestic satellite stereo image extraction does not exceed 0.5m.

[0004] Currently, Chinese patent application number CN116542536A discloses a method and device for evaluating the implementation effect of sponge city construction based on high-resolution remote sensing imagery. This method includes acquiring the underlying surface results of the sponge city based on high-resolution remote sensing imagery, extracting high-precision urban topography from satellite stereo imagery, and coupling a hydrological and hydrodynamic model to simulate total runoff. However, the high-resolution remote sensing data mentioned in the above method includes satellite imagery data from Gaofen-7 (0.65m resolution) and WorldView-2 (0.5m resolution). This level of precision is only suitable for comprehensive evaluation of the entire project or area, and is insufficient for simulating the total runoff control requirements of individual facilities or higher-precision models.

[0005] In summary, existing methods for acquiring underlying surface data of sponge cities using satellite remote sensing data are insufficient for simulating total runoff control requirements for individual facilities or higher-precision models, and cannot meet the requirements for small-scale runoff simulation. Summary of the Invention

[0006] To address the problems existing in the above-mentioned fields, this invention proposes a method and system for evaluating runoff in sponge cities. This method can solve the technical problem that the existing methods for obtaining underlying surface data of sponge cities using satellite remote sensing data are insufficient for simulating the total runoff control requirements of individual facilities or higher-precision models, and cannot meet the requirements for small-scale runoff simulation.

[0007] To address the aforementioned technical problems, this invention discloses a method for evaluating runoff in sponge cities, comprising the following steps:

[0008] Based on UAV oblique photography technology, image data of the sponge city research area was obtained;

[0009] The acquired image data is processed to obtain the DOM and DEM of the sponge city study area;

[0010] Based on the DOM and DEM of the study area, ArcGIS software was used to divide the sub-catchment areas and extract the geometric parameter data of the sub-catchment areas.

[0011] By conducting soil infiltration experiments and fitting the Horton equation, we obtained the infiltration parameter data required for the SWMM model based on UAV oblique photogrammetry.

[0012] Geometric and infiltration parameter data were input into the SWMM model, and the remaining parameters of the SWMM model were manually calibrated. Rainfall data were added to construct an SWMM model based on UAV oblique photogrammetry technology. Based on the constructed SWMM model based on UAV oblique photogrammetry technology, the runoff generation, confluence, and pipe network confluence processes of surface runoff in the study area were simulated to evaluate the total runoff control target of sponge city.

[0013] Preferably, acquiring image data of the sponge city research area includes the following steps:

[0014] The drone was set up to continuously change the center of the circle and simultaneously collect images of the study area from five directions: vertical, front, back, left, and right.

[0015] Check the tilt angle, yaw angle, overlap, flight path curvature, altitude difference, color consistency, and image sharpness, as well as whether there are any shadows or reflections.

[0016] Preferably, obtaining the DOM and DEM of the sponge city research area includes the following steps:

[0017] Create new projects and new blocks in Smart 3D software;

[0018] Import clear image data, accurate POS data, and high-precision control point data from UAV aerial photography to complete the establishment of the new project;

[0019] Aerial triangulation calculations are performed in Smart 3D software to extract feature points, match image pairs, and perform dense matching of corresponding points.

[0020] The aerial triangulation results report is obtained through the cloud-based Earth. When the aerial triangulation process is completed, the real scene model is segmented into blocks, and a new generation task is directly submitted to obtain the real scene 3D model and DSM point cloud.

[0021] Based on high-density DSM point cloud, DOM is generated through true orthophoto correction technology, including digital differential correction, center projection correction to orthophoto projection, detection of image occlusion areas and compensation, to obtain a high-precision DOM model.

[0022] After filtering the DSM point cloud, point cloud data of non-ground points such as buildings and trees can be obtained, and then the digital elevation model (DEM) of the photographed area can be obtained.

[0023] Preferably, the process of dividing sub-catchment areas and extracting their geometric parameter data includes the following steps:

[0024] Based on the topography and pipeline distribution of the study area, and taking into account both the Thiessen polygon method and the sub-catchment area division method based on surface water flow direction, sub-catchment areas are divided.

[0025] Based on the centimeter-level DEM obtained by UAV oblique photogrammetry, sub-catchment areas are extracted using the hydrological analysis tools in ArcGIS software. The specific steps include:

[0026] Use the depression-filling tool to eliminate minor defects in DEM data;

[0027] Flow direction data is obtained using a flow direction tool, and the algorithm used is the classic D8 algorithm;

[0028] Use traffic tools to obtain traffic data;

[0029] Use the raster calculator and set a reasonable threshold to extract the confluence raster data;

[0030] Use the river linking tool to obtain the spillway data;

[0031] Based on flow direction data and dumping point data, the sub-catchment areas of the study area were extracted using the watershed tool;

[0032] The geometric parameters of the sub-catchment area are obtained from DOM and DEM, including the area, characteristic width, average slope and impermeable area ratio of the sub-catchment area;

[0033] To calculate the area of ​​a sub-catchment, open the sub-catchment vector layer, select the area field, and use the field calculator tool to calculate the area of ​​each sub-catchment.

[0034] The characteristic width is calculated as the ratio of the sub-catchment area to the longest runoff length of the sub-catchment.

[0035] The maximum runoff length is calculated based on the DEM. First, the flow direction and flow rate tools in the hydrological analysis tools are used to obtain the runoff raster. Then, the raster calculator is used to extract the runoff data and the raster turning line tool is used to convert it into vector data. Next, the analysis tool - overlay analysis - identifier is used to extract the runoff corresponding to each sub-catchment. Then, the computational geometry tool in the attribute table is used to calculate the length. Finally, the runoff is classified and summarized according to the sub-catchment to obtain the maximum runoff length of each sub-catchment.

[0036] To calculate the average slope, firstly, the slope tool was used in the spatial analysis tool - surface analysis - slope tool, with the DEM as input data, to obtain the slope data within the study area; secondly, the slope data was converted into vector data, and the slope corresponding to each sub-catchment was extracted using the analysis tool - overlay analysis - identifier; finally, the average value of the slope field in the attribute table was calculated according to the sub-catchment.

[0037] To calculate the proportion of impervious areas, the study area was divided into land types, and DOM was used for extraction to calculate the proportion of impervious areas.

[0038] Preferably, the acquisition of the infiltration parameter data includes the following steps:

[0039] Data was collected through soil infiltration experiments, and the Horton equation formula was fitted, including steady infiltration rate and infiltration attenuation coefficient, etc.

[0040] The SWMM model based on UAV oblique photogrammetry technology is used to simulate infiltration using the classic Horton equation. Soil samples from the evaluation area are collected for experimental testing, and the parameters of the Horton infiltration model are calibrated using regression method.

[0041] The formula for calculating the Horton equation is as follows:

[0042] f t =(f a -f b )e -kt +f b

[0043] In the formula, f t f is the infiltration rate at time t, in mm / h. a The initial infiltration rate is expressed in mm / h; k is the infiltration attenuation coefficient, usually determined experimentally, with units of 1 / h; f b The infiltration rate is measured in mm / h; t represents the rainfall duration in hours.

[0044] A checkerboard sampling method was used to uniformly mix soil samples collected from multiple points in the study area for soil infiltration tests.

[0045] In the experiment, a one-dimensional soil column device and a water supply tank were used. The top of the soil column was quickly filled with a 2cm high water layer, and the valve of the Marshall bottle was opened to release water. The water head was maintained at 2cm through the water supply tank. During the experiment, the water level change after the start of water supply was recorded, and the water supply volume was read from the scale on the water supply tank. Initially, the data was recorded every 10 seconds, then every 30 seconds after 1 minute, and then every minute after 3 minutes, until the soil sample was completely infiltrated and the infiltration rate was stable.

[0046] At the end of the experiment, the soil seepage rate was determined based on the change in water level readings. The data was then applied to the Horton seepage formula for parameter fitting. The fitted parameters were then added to the SWMM model based on UAV oblique photogrammetry technology for soil infiltration simulation.

[0047] Preferably, the evaluation of the total runoff control target for sponge cities includes the following steps:

[0048] The remaining parameters of the SWMM were manually calibrated, rainfall data were added, and the SWMM model based on UAV oblique photogrammetry technology was completed to accurately simulate the surface runoff generation, confluence and pipe network confluence process.

[0049] The formula for calculating the total annual runoff control rate within the study area is as follows:

[0050]

[0051] In the formula, α represents the annual runoff volume control rate, in percentage (%); VO Annual emissions, in cubic meters. 3 ;I A Total annual rainfall, in meters (m). 3 ;

[0052] The higher the annual runoff volume control rate α, the greater the annual discharge V. O The smaller the value, the better the rainwater control effect in the study area.

[0053] Preferably, it also includes a sponge city runoff assessment system, comprising:

[0054] The data acquisition module is used to acquire image data of the sponge city research area using UAV oblique photography technology.

[0055] The data processing module is used to process the acquired image data to obtain the DOM and DEM of the sponge city research area;

[0056] The model building module is used to divide sub-catchments and extract geometric parameter data of the sub-catchments using ArcGIS software based on the DOM and DEM of the sponge city research area; to obtain the infiltration parameter data required for the SWMM model based on UAV oblique photogrammetry through soil infiltration experiments; to input the geometric parameter data and infiltration parameter data into the SWMM model, to manually calibrate the remaining parameters of the SWMM model, to add rainfall data, and to build the SWMM model based on UAV oblique photogrammetry.

[0057] The evaluation results module is used to evaluate the total runoff control targets of sponge cities by simulating the generation, confluence, and pipe network confluence processes of surface runoff in the study area based on the constructed SWMM model based on UAV oblique photography technology.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] This invention utilizes UAV oblique photogrammetry to acquire image data of the research area. The UAV captures images from different angles using a camera, allowing the acquisition of top information and side textures of ground objects within a single photograph. Based on the obtained high-precision DOM and DEM of the photographed area, sub-catchment areas are divided. ArcGIS technology is used for feature extraction to obtain geometric parameter data for each sub-catchment area. Soil infiltration experiments are conducted to obtain the necessary infiltration parameter data based on UAV oblique photogrammetry. The geometric and infiltration parameter data are input into the SWMM model, and the remaining parameters of the SWMM model are manually calibrated. Rainfall data is added to complete the construction of the SWMM model based on UAV oblique photogrammetry. This model can accurately simulate surface runoff generation, confluence, and pipe network confluence processes, thereby precisely obtaining the simulation results of sponge city runoff. This method improves the accuracy of sponge city runoff simulation assessment and can meet the requirements for total runoff control in sponge city construction, whether for individual facilities or higher-precision models. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0061] Figure 2 A schematic diagram of an SWMM model based on UAV oblique photogrammetry constructed for an embodiment of the present invention;

[0062] Figure 3 This is a scatter plot showing the seepage velocity of the soil sample selected for this invention as a function of time. Detailed Implementation

[0063] The following will refer to the appendices in the embodiments of the present invention. Figures 1-3 The technical solutions in the embodiments of the present invention will be clearly and completely described. It should be understood that the terminology used in the present invention is only for describing particular implementation methods and is not intended to limit the present invention.

[0064] like Figure 1 As shown in the figure, this embodiment of the invention provides a method for evaluating runoff in sponge cities, including the following steps:

[0065] Step 1: Image Data Acquisition for the Sponge City Research Area Based on UAV Oblique Photography Technology

[0066] Unmanned aerial vehicle (UAV) oblique photography refers to the process by which UAVs simultaneously acquire images from five directions: vertical, front, back, left, and right. The process involves camera calibration, setting aerial photography technical parameters and data transmission, checking flight quality and image quality, and finally obtaining image data.

[0067] Step 2: Image data processing to obtain the DOM and DEM of the sponge city study area.

[0068] The Smart 3D data processing and modeling software was selected to process the oblique photogrammetry image data to build a model. The aerial triangulation verification and point cloud generation were used to process the images obtained from the oblique photogrammetry aerial photography, and a high-density digital surface model (DSM) point cloud and a 3D model were produced.

[0069] Building upon the results of high-density DSM point cloud, a DOM is further generated through orthographic correction technology. The specific process includes digital differential correction of the image, correcting the central projection to orthographic projection, and using the technology of neighboring images or digital images to compensate for the occluded area in the detected image occlusion area, thereby obtaining a high-precision DOM model.

[0070] After filtering the DSM point cloud, point cloud data with non-ground points such as buildings and trees removed can be obtained. With ground point cloud data, a digital elevation model (DEM) of the photographed area can be obtained.

[0071] Step 3: Based on the DOM and DEM, use ArcGIS software to divide the sub-catchments and extract the geometric parameter data of the sub-catchments;

[0072] Based on the topography and pipeline distribution of the study area, and considering both the Thiessen polygon method and the sub-catchment division method based on surface water flow direction, sub-catchment areas were delineated. Using centimeter-level DEMs obtained from UAV oblique photogrammetry, sub-catchment areas were extracted using the hydrological analysis tools in ArcGIS software. Specific steps included:

[0073] (1) Use the depression filling tool to eliminate minor defects in the DEM data;

[0074] (2) Use the flow direction tool to obtain flow direction data. The algorithm adopts the classic D8 algorithm.

[0075] (3) Use traffic tools to obtain traffic data;

[0076] (4) Use a raster calculator and set a reasonable threshold to extract the confluence raster data;

[0077] (5) Use the river linking tool to obtain the dumping point data;

[0078] (6) Based on flow direction data and dumping point data, the sub-catchment areas of the study area are extracted using the watershed tool.

[0079] By statistically analyzing big data and organizing rainfall and pipeline data in the study area, and combining the high-precision urban DEM and DOM constructed by UAV oblique photogrammetry, geometric parameters of the sub-catchment area of ​​the SWMM model were collected.

[0080] The geometric parameters of the sub-catchment area are obtained from DOM and DEM, including the area, characteristic width, average slope, and proportion of impermeable area of ​​the sub-catchment area.

[0081] Specifically, based on the already photographed regional DOM and DEM, ArcGIS software was used to extract the geometric parameters of the sub-catchment areas required for the operation of the SWMM model within the study area, thereby constructing an SWMM model based on UAV oblique photogrammetry technology; the specific steps are as follows:

[0082] (1) Calculate the area of ​​sub-catchment areas: Open the sub-catchment vector layer, select the area field, and use the "Field Calculator" tool to calculate the area of ​​each sub-catchment area.

[0083] (2) Calculation of characteristic width: The formula for calculating the characteristic width of the sub-catchment area is as follows:

[0084] Sub-catchment characteristic width = Sub-catchment area / longest runoff length of sub-catchment

[0085] The maximum runoff length is calculated based on the DEM. First, the flow direction and flow rate tools in the hydrological analysis tools are used to obtain the runoff raster. Then, the raster calculator is used to extract the runoff data and the raster turning line tool is used to convert it into vector data. Next, the analysis tool - overlay analysis - identifier is used to extract the runoff corresponding to each sub-catchment. Then, the computational geometry tool in the attribute table is used to calculate the length. Finally, the maximum runoff length of each sub-catchment is obtained by classifying and summarizing the data according to the sub-catchment.

[0086] (3) Average slope calculation: First, use the spatial analysis tool - surface analysis - slope tool with DEM as input data to obtain the slope data within the study area; second, convert the slope data into vector data, and use the analysis tool - overlay analysis - identifier to extract the slope corresponding to each sub-catchment area; finally, calculate the average value of the slope field in the attribute table according to the sub-catchment area.

[0087] (4) Calculation of the proportion of impervious area: Divide the land types in the study area, extract the DOM, and calculate the proportion of impervious area.

[0088] Step 4: Obtain the required infiltration parameter data for the SWMM model based on UAV oblique photogrammetry through soil infiltration experiments.

[0089] Among the data requiring further calibration in the SWMM model based on UAV oblique photogrammetry technology are the steady-state infiltration rate and infiltration attenuation coefficient. Through soil infiltration experiments, the Horton equation is fitted to obtain the infiltration parameter data needed to construct the SWMM model for the study area.

[0090] The SWMM model was used to simulate infiltration using the classic Horton equation, and soil samples were collected from the evaluation area for experimental determination. The parameters of the Horton infiltration model were calibrated using the regression method.

[0091] The formula for calculating the Horton equation is as follows:

[0092] f t =(f a -f b ) e -kt +f b (1)

[0093] In the formula, f t f is the infiltration rate at time t, in mm / h. a The initial infiltration rate is expressed in mm / h; k is the infiltration attenuation coefficient, usually determined experimentally, with units of 1 / h; f b The infiltration rate is measured in mm / h; t represents the rainfall duration in hours.

[0094] Specifically, this application uses a checkerboard sampling method to uniformly mix soil samples collected from multiple points in the study area for soil infiltration tests;

[0095] In the experiment, a one-dimensional soil column device and a water supply tank were used. The top of the soil column was quickly filled with a 2cm high water layer, and the valve of the Marshall bottle was opened to release water. The water head was maintained at 2cm through the water supply tank. During the experiment, the water level change after the start of water supply was recorded, and the water supply volume was read from the scale on the water supply tank. Initially, the data was recorded every 10 seconds, then every 30 seconds after 1 minute, and then every minute after 3 minutes, until the soil sample was completely infiltrated and the infiltration rate was stable.

[0096] At the end of the experiment, the soil seepage rate was determined based on the change in water level readings. The data was then applied to the Horton seepage formula for parameter fitting. The fitted parameters were added to the SWMM model for soil infiltration simulation.

[0097] Step 5: Conduct runoff simulation in the SWMM model based on UAV oblique photogrammetry technology to evaluate the total runoff control target of sponge city.

[0098] The simulation of surface runoff generation and confluence processes in the study area includes the following steps:

[0099] The remaining parameters of the SWMM were manually calibrated, rainfall data was added, and the SWMM model based on UAV oblique photogrammetry was completed, as shown below. Figure 2 As shown, it can accurately simulate the processes of surface runoff generation, confluence, and pipeline confluence.

[0100] During the SWMM simulation, rain gauges need to be configured. Setting up rain gauges requires inputting rainfall data in the "Data Source" field. Rainfall data can be either actual measured rainfall data or rainfall data synthesized using a typical rainfall model.

[0101] Based on the constructed SWMM model using UAV oblique photogrammetry technology, runoff volume simulation was performed to evaluate whether the total runoff control target was met.

[0102] The SWMM software simulation steps include:

[0103] (1) SWMM project defaults. In this application, the default ID is set in the setting of the label prefix in the new project. When it is set for the first time, the corresponding default ID label prefix is ​​assigned.

[0104] (2) Add visual objects to the SWMM software. Add objects such as rain gauges, pipe sections, junctions, outlets, and canals to the sub-catchment areas of the generated SWMM model based on UAV oblique photogrammetry technology, and add the objects to the attribute editor.

[0105] (3) SWMM software performs simulation. At the top of the SWMM software, select the "Perform Simulation" option, and the simulation task will be performed according to the selected project.

[0106] After the task is completed, a running status interface will appear. If the error is within the range specified in the SWMM manual, the simulation is successful. After the simulation is successful, you can view the project status report and summary report to obtain the simulation summary report and other results output. Combined with the evaluation methods of runoff total volume control and runoff volume control in sponge city construction, the control objectives can be evaluated.

[0107] Example

[0108] S1: Since this application is highly dependent on the accuracy of data collected by drones, it is required to use drones with higher precision to acquire image data. It is recommended to use DJI Matrice drones.

[0109] This embodiment uses a DJI Inspire 2 drone equipped with a gimbal camera as an aerial sensor to acquire ground image data. The flight speed was set to 10 m / s, with a lateral overlap of 50% and a longitudinal overlap of 76%. The study area was a teaching building, and the flight altitude was selected as 100 meters. To ensure the overlap rate, a combination of fixed-flight and manual flight modes was used, taking one photo every 2 seconds. During this period, a circling method was used for manual flight to conduct aerial surveys of the study area in five directions: vertical, forward, backward, left, and right. The image position data during the drone's oblique aerial photography was automatically generated by the drone and corresponded to each photo, ultimately yielding 12.36G of image data. The tilt angle, yaw angle, overlap, flight path curvature, flight altitude difference, color consistency, and image sharpness were checked, as well as for issues such as shadows and reflections.

[0110] S2: In this embodiment, a new project is first created in the Smart 3D software, and clear aerial image data, correct POS data, and high-precision ground control point data are imported to complete the establishment of the new project. Then, aerial triangulation calculations are performed in the Smart 3D software, including feature point extraction, image pair matching, and dense matching of corresponding points. An aerial triangulation result report is obtained via a cloud-based Earth system, showing an average projection error of less than one pixel, indicating that the overall accuracy of the image data meets the standard. After the aerial triangulation process is completed, the real-world model can be segmented, and a new generation task can be directly submitted to obtain a real-world 3D model and a DSM point cloud.

[0111] Based on high-density DSM point clouds, a DOM (Digital Elevation Model) is generated using true orthographic correction techniques, including digital differential correction, central projection correction to orthographic projection, and detection and compensation of image occlusion areas, resulting in a high-precision DOM model. After filtering the DSM point clouds, point cloud data with non-ground points such as buildings and trees removed is obtained, thus yielding a digital elevation model (DEM) of the photographed area.

[0112] S3: In this embodiment, considering both the Thiessen polygon method and the sub-catchment area division method based on surface water flow direction, and based on the centimeter-level DEM obtained by UAV oblique photogrammetry, the hydrological analysis tools of ArcGIS software are used to extract sub-catchment areas, and the study area is generalized into 62 sub-catchment areas, 58 nodes, 61 pipe segments, and 4 discharge outlets.

[0113] Based on the already photographed regional DOM and DEM, ArcGIS software was used to extract the geometric parameter data of the sub-catchment areas required for the operation of the SWMM model within the study area, and then an SWMM model based on UAV oblique photogrammetry technology was constructed.

[0114] Table 1. Results of the generalized sub-catchment area

[0115]

[0116]

[0117] S4: In this embodiment, soil samples from the sponge city research area are obtained through checkerboard sampling, and soil specimens are prepared before testing begins.

[0118] The soil infiltration results selected in this invention are shown in Table 2.

[0119] Table 2. Infiltration results of soil samples selected in this invention.

[0120]

[0121] like Figure 3 As shown, this is a scatter plot of the seepage rate over time for the soil samples corresponding to Table 2.

[0122] After fitting the soil seepage data and undergoing final calibration, f is obtained. b =85, f a =72699, k=718, R 2 =0.9864, substituting into formula (1), we obtain the Horton infiltration equation for the soil selected in this embodiment:

[0123] f t =72614*e -718*t +85 (2)

[0124] S5: Simulate runoff volume in the SWMM model to evaluate whether the total runoff target has been met.

[0125] For the simulation, the Horton model was selected as the infiltration model, and the dynamic wave method was used for calculating the pipe network runoff. The Chicago synthetic storm process line, the most common method used in SWMM modeling to simulate rainfall data, was adopted. Typical rainfall patterns of the Chicago storm under five different return periods (2-year, 5-year, 10-year, 20-year, and 50-year) were selected, and a non-uniform design rainfall pattern was derived based on the relationship between rainfall intensity, duration, and frequency. The total rainfall duration was 120 minutes, and a peak rainfall coefficient of 0.4 was selected.

[0126] In this embodiment, rainfall data is added using the Chicago rain pattern simulation. The general formula for the intensity of a Chicago rain pattern storm is as follows:

[0127]

[0128] In the formula, q is the design rainfall intensity, in L / (s·hm2); t is the rainfall duration, in min; P is the design return period; A1 is the design rainfall amount with a return period of 1 year, in mm; C is the rainfall variation parameter; b and n are the time parameter and the rainfall attenuation index, respectively.

[0129] The formula for the intensity of rainstorms in the city where this invention is implemented is as follows:

[0130]

[0131] The "Evaluation Standard for Sponge City Construction" GB / T51345-2018 stipulates that the evaluation of the annual runoff control rate of drainage zones using the model simulation method requires continuous rainfall monitoring data for at least the past 10 years with a step size of 1 minute, 5 minutes, or 1 hour. Since accurate measured rainfall data could not be collected in the study area of ​​this application's embodiment, and no prior measured data was available, a synthetic design rainfall simulation was used.

[0132] Based on the urban storm intensity formula for the selected study area, the runoff generation and confluence processes of the city's surface runoff are calculated.

[0133] Set the default settings for the SWMM software, add visualization objects to the SWMM model, perform the simulation, obtain results such as runoff control rate, and compare them with the target value.

[0134] The annual runoff control rate of the study area is calculated using the following formula:

[0135]

[0136] In the formula, α represents the annual runoff volume control rate, in percentage (%); V O Annual emissions, in cubic meters. 3 ;I A Total annual rainfall, in meters (m). 3 The higher the annual runoff control rate α, the greater the annual discharge V. O The smaller the value, the better the rainwater control effect in the study area.

[0137] The simulation and calculation results of runoff under different return periods are shown in Table 3.

[0138] Table 3. Simulation results of surface runoff at different return periods

[0139]

[0140] According to the requirements of the "Special Plan for Sponge City Construction in the Central Urban Area of ​​Xuzhou", the annual runoff volume control target for this study area is 75%, which corresponds to a designed rainfall of 27.3 mm. Therefore, as shown in Table 3, the annual runoff volume control in the sponge city study area of ​​this embodiment does not meet the sponge city control requirements.

[0141] This application proposes a high-precision model to simulate runoff using 3D modeling based on UAV oblique photogrammetry and SWMM model simulation technology, evaluating whether the annual runoff volume control rate meets the design requirements of sponge cities from the perspective of runoff volume. High-precision, cost-effective UAV oblique photogrammetry is employed to obtain a high-resolution digital elevation model. ArcGIS software is used to divide sub-catchments and extract their geometric parameters. Through soil infiltration experiments, the Horton equation is fitted to obtain the infiltration parameter data required for the SWMM model based on UAV oblique photogrammetry. The remaining parameters of the SWMM model are manually calibrated, and rainfall data is added to construct the SWMM model based on UAV oblique photogrammetry. The geometric and infiltration parameter data are used as inputs to the SWMM model based on UAV oblique photogrammetry. By simulating the generation, confluence, and pipe network confluence processes of surface runoff in the study area, the runoff volume control target of sponge cities is evaluated. The model constructed using this method can improve the simulation accuracy to the centimeter level, which is of great significance for future high-precision urban stormwater simulation research and has high application value and prospects in small-scale sponge city design.

[0142] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

[0143] Furthermore, unless otherwise stated, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. All references to this specification are incorporated by way of citation to disclose and describe methods relating to those references. In the event of any conflict with any incorporated reference, the content of this specification shall prevail.

Claims

1. A method for evaluating runoff in sponge cities, characterized in that, Includes the following steps: Based on UAV oblique photography technology, image data of the sponge city research area was obtained; The acquired image data is processed to obtain the DOM and DEM of the sponge city study area; Based on the DOM and DEM of the study area, ArcGIS software was used to divide the sub-catchment areas and extract the geometric parameter data of the sub-catchment areas. By conducting soil infiltration experiments and fitting the Horton equation, we obtained the infiltration parameter data required for the SWMM model based on UAV oblique photogrammetry. Geometric and infiltration parameter data were input into the SWMM model, and the remaining parameters of the SWMM model were manually calibrated. Rainfall data were added to construct an SWMM model based on UAV oblique photogrammetry technology. Based on the constructed SWMM model based on UAV oblique photogrammetry technology, the runoff generation, confluence, and pipe network confluence processes of surface runoff in the study area were simulated to evaluate the total runoff control target of sponge city.

2. The method for evaluating runoff in sponge cities according to claim 1, characterized in that, The acquisition of image data of the sponge city research area includes the following steps: The drone was set up to continuously change the center of the circle and simultaneously collect images of the study area from five directions: vertical, front, back, left, and right. Check the tilt angle, yaw angle, overlap, flight path curvature, altitude difference, color consistency, and image sharpness, as well as whether there are any shadows or reflections.

3. The method for evaluating runoff in sponge cities according to claim 2, characterized in that, Obtaining the DOM and DEM of the sponge city research area includes the following steps: Create new projects and new blocks in Smart 3D software; Import clear image data, accurate POS data, and high-precision control point data from UAV aerial photography to complete the establishment of the new project; Aerial triangulation calculations are performed in Smart 3D software to extract feature points, match image pairs, and perform dense matching of corresponding points. The aerial triangulation results report is obtained through the cloud-based Earth. When the aerial triangulation process is completed, the real scene model is segmented into blocks, and a new generation task is directly submitted to obtain the real scene 3D model and DSM point cloud. Based on high-density DSM point cloud, DOM is generated through true orthophoto correction technology, including digital differential correction, center projection correction to orthophoto projection, detection of image occlusion areas and compensation, to obtain a high-precision DOM model. After filtering the DSM point cloud, point cloud data of non-ground points such as buildings and trees can be obtained, and then the digital elevation model (DEM) of the photographed area can be obtained.

4. The method for evaluating runoff in sponge cities according to claim 3, characterized in that, The process of dividing sub-catchments and extracting their geometric parameter data includes the following steps: Based on the topography and pipeline distribution of the study area, and taking into account both the Thiessen polygon method and the sub-catchment area division method based on surface water flow direction, sub-catchment areas are divided. Based on the centimeter-level DEM obtained by UAV oblique photogrammetry, sub-catchment areas are extracted using the hydrological analysis tools in ArcGIS software. The specific steps include: Use the depression-filling tool to eliminate minor defects in DEM data; Flow direction data is obtained using a flow direction tool, and the algorithm used is the classic D8 algorithm; Use traffic tools to obtain traffic data; Use the raster calculator and set a reasonable threshold to extract the confluence raster data; Use the river linking tool to obtain the spillway data; Based on flow direction data and dumping point data, the sub-catchment areas of the study area were extracted using the watershed tool; The geometric parameters of the sub-catchment area are obtained from DOM and DEM, including the area, characteristic width, average slope and impermeable area ratio of the sub-catchment area; To calculate the area of ​​a sub-catchment, open the sub-catchment vector layer, select the area field, and use the field calculator tool to calculate the area of ​​each sub-catchment. The characteristic width is calculated as the ratio of the sub-catchment area to the longest runoff length of the sub-catchment. The maximum runoff length is calculated based on the DEM. First, the flow direction and flow rate tools in the hydrological analysis tools are used to obtain the runoff raster. Then, the raster calculator is used to extract the runoff data and the raster turning line tool is used to convert it into vector data. Next, the analysis tool - overlay analysis - identifier is used to extract the runoff corresponding to each sub-catchment. Then, the computational geometry tool in the attribute table is used to calculate the length. Finally, the runoff is classified and summarized according to the sub-catchment to obtain the maximum runoff length of each sub-catchment. To calculate the average slope, firstly, the slope tool was used in the spatial analysis tool - surface analysis - slope tool, with the DEM as input data, to obtain the slope data within the study area; secondly, the slope data was converted into vector data, and the slope corresponding to each sub-catchment was extracted using the analysis tool - overlay analysis - identifier; finally, the average value of the slope field in the attribute table was calculated according to the sub-catchment. To calculate the proportion of impervious areas, the study area was divided into land types, and DOM was used for extraction to calculate the proportion of impervious areas.

5. The method for evaluating runoff in sponge cities according to claim 4, characterized in that, The acquisition of the infiltration parameter data includes the following steps: Data was collected through soil infiltration experiments, and the Horton equation formula was fitted, including steady infiltration rate and infiltration attenuation coefficient, etc. The SWMM model based on UAV oblique photogrammetry technology is used to simulate infiltration using the classic Horton equation. Soil samples from the evaluation area are collected for experimental testing, and the parameters of the Horton infiltration model are calibrated using regression method. The formula for calculating the Horton equation is as follows: f t =(f a -f b )e -kt +f b In the formula, f t f is the infiltration rate at time t, in mm / h. a The initial infiltration rate is expressed in mm / h; k is the infiltration attenuation coefficient, usually determined experimentally, with units of 1 / h; f b The infiltration rate is measured in mm / h; t represents the rainfall duration in hours. A checkerboard sampling method was used to uniformly mix soil samples collected from multiple points in the study area for soil infiltration tests. In the experiment, a one-dimensional soil column device and a water supply tank were used. The top of the soil column was quickly filled with a 2cm high water layer, and the valve of the Marshall bottle was opened to release water. The water head was maintained at 2cm through the water supply tank. During the experiment, the water level change after the start of water supply was recorded, and the water supply volume was read from the scale on the water supply tank. Initially, the data was recorded every 10 seconds, then every 30 seconds after 1 minute, and then every minute after 3 minutes, until the soil sample was completely infiltrated and the infiltration rate was stable. At the end of the experiment, the soil seepage rate was determined based on the change in water level readings. The data was then applied to the Horton seepage formula for parameter fitting. The fitted parameters were then added to the SWMM model based on UAV oblique photogrammetry technology for soil infiltration simulation.

6. The method for evaluating runoff in sponge cities according to claim 5, characterized in that, The evaluation of the runoff volume control target for sponge cities includes the following steps: The remaining parameters of the SWMM were manually calibrated, rainfall data were added, and the SWMM model based on UAV oblique photogrammetry technology was completed to accurately simulate the surface runoff generation, confluence and pipe network confluence process. The formula for calculating the total annual runoff control rate within the study area is as follows: In the formula, α represents the annual runoff volume control rate, in percentage (%); V O Annual emissions, in cubic meters. 3 ;I A Total annual rainfall, in meters (m). 3 ; The higher the annual runoff volume control rate α, the greater the annual discharge V. O The smaller the value, the better the rainwater control effect in the study area.

7. A sponge city runoff evaluation system, characterized in that, include: The data acquisition module is used to acquire image data of the sponge city research area using UAV oblique photography technology. The data processing module is used to process the acquired image data to obtain the DOM and DEM of the sponge city research area; The model building module is used to divide sub-catchments and extract geometric parameter data of the sub-catchments using ArcGIS software based on the DOM and DEM of the sponge city research area; to obtain the infiltration parameter data required for the SWMM model based on UAV oblique photogrammetry through soil infiltration experiments; to input the geometric parameter data and infiltration parameter data into the SWMM model, to manually calibrate the remaining parameters of the SWMM model, to add rainfall data, and to build the SWMM model based on UAV oblique photogrammetry. The evaluation results module is used to evaluate the total runoff control targets of sponge cities by simulating the generation, confluence, and pipe network confluence processes of surface runoff in the study area based on the constructed SWMM model based on UAV oblique photography technology.

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