A method for analyzing urban waterlogging considering the temporal and spatial distribution characteristics of rainfall

Abstract

This application discloses a method for analyzing urban waterlogging that considers the spatiotemporal distribution characteristics of rainfall. The method relates to the field of urban waterlogging analysis and includes constructing an uncertain spatiotemporal distribution structure of rainfall based on a designed rainstorm scenario and a synthetic rainfall model for the city to be analyzed; constructing an urban hydrological and hydrodynamic model based on the basic data of the city to be analyzed and a stormwater and flood management model, taking the uncertain spatiotemporal distribution structure of rainfall as input; constructing a pipe network drainage evaluation index system; determining the spatiotemporal distribution characteristics of waterlogging and overflow based on the urban hydrological and hydrodynamic model; determining key indicators in the pipe network drainage evaluation index system based on the spatiotemporal distribution characteristics of waterlogging and overflow; analyzing the value ranges of key indicators based on the uncertain spatiotemporal distribution structure of rainfall, and evaluating the comprehensive pipe network drainage performance of the city to be analyzed based on these value ranges. This application can improve the adaptability of urban waterlogging analysis results in changing environments.

Description

Technical Field

[0001] The present application relates to the field of urban waterlogging analysis, and in particular to an urban waterlogging analysis method that takes into account the temporal and spatial distribution characteristics of rainfall. Background Art

[0002] Extreme rainstorms brought on by climate change lead to the combined effects of river basin flooding and urban waterlogging, placing enormous pressure on urban flood mitigation efforts and exacerbating the frequency and severity of urban waterlogging disasters. Influenced by large-scale land surface hydrological processes and small- and medium-scale weather systems, urban rainfall processes exhibit significant spatial and temporal heterogeneity and inconsistency. Extreme rainfall is a direct cause of urban waterlogging, and the complex spatial and temporal distribution of rainfall has a significant impact on urban hydrological and hydrodynamic processes. Specifically, the following are reflected: 1) The temporal distribution and rainfall pattern characteristics (amount, duration, peak intensity, and concentration) of rainfall have a direct impact on the mechanisms that induce urban waterlogging; 2) Due to the limitations of urban building density and observation conditions, the spatial distribution differences of rainstorms within cities are often overlooked. Consequently, insufficient monitoring coverage and local regulation capabilities exacerbate the risk of waterlogging in vulnerable areas.

[0003] Currently, drainage system evaluations often use single design rainfall events as input, or utilize long-term data series from multiple rainfall events, without carefully considering the impact of rainfall uncertainty. Urban rainfall and flooding processes are dynamic and uncertain, yet stormwater and drainage systems are typically designed under static conditions, and their corresponding controls are often based on static rules. Therefore, faced with complex and variable uncertain rainfall inputs, system controls also face corresponding operational risks and optimization space. This changing environment introduces uncertain external conditions to urban stormwater management. Solutions require substantial construction, operation, and maintenance costs, requiring significant upfront investment and placing high demands on background conditions such as construction and renovation sites. Therefore, research on urban flooding analysis methods that consider the spatiotemporal distribution characteristics of uncertain rainfall is essential. Summary of the Invention

[0004] The purpose of this application is to provide an urban waterlogging analysis method that takes into account the temporal and spatial distribution characteristics of rainfall, which can improve the adaptability of urban waterlogging analysis results in a changing environment.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] This application provides an urban waterlogging analysis method that considers the temporal and spatial distribution characteristics of rainfall. The urban waterlogging analysis method that considers the temporal and spatial distribution characteristics of rainfall includes:

[0007] Constructing the uncertain spatial and temporal distribution structure of rainfall based on the designed rainstorm scenario and synthetic rainfall model of the city to be analyzed;

[0008] Based on the basic data of the city to be analyzed and the storm flood management model, an urban hydrological and hydrodynamic model with the uncertain spatial and temporal distribution structure of rainfall as input is constructed;

[0009] Constructing a drainage network evaluation index system for the city to be analyzed; the drainage network evaluation index system includes: a total overflow index, a total waterlogging index, an overflow distribution index, a waterlogging distribution index, a waterlogging pipeline ratio index, and a waterlogging potential hazard index;

[0010] Determine the spatiotemporal distribution characteristics of waterlogging and overflow based on the urban hydrological and hydrodynamic model; and determine the key indicators in the drainage network evaluation index system based on the spatiotemporal distribution characteristics of waterlogging and overflow;

[0011] The value ranges of key indicators are analyzed based on the uncertain spatiotemporal distribution structure of rainfall, and the comprehensive performance of the drainage network in the city to be analyzed is evaluated based on the value ranges.

[0012] Optionally, the step of constructing an uncertain rainfall spatiotemporal distribution structure based on a designed rainstorm scenario and a synthetic rainfall model for the city to be analyzed specifically includes:

[0013] Determine the design stormwater scenario using the design stormwater formula for the city to be analyzed;

[0014] Using the formula Determine the synthetic rainfall model;

[0015] in, is the formula for spatially non-uniform rainfall intensity, , is the design rainstorm intensity determined by the rainstorm intensity formula, D is the domain of the two-dimensional truncated Gaussian distribution, A is the basin area, , is the scaling function of the Gaussian distribution, ensuring that the integral of the distribution in the domain is 1, are the mean and variance of the Gaussian distribution, ( ) is the spatial coordinate of the rainstorm center, are the coordinates of any point in space, is the rainfall duration, is the Gaussian distribution function.

[0016] Optionally, the design rainstorm formula is: ;

[0017] in, To design the rainstorm intensity, is the design return period, 、 、 、 As a parameter.

[0018] Optionally, the basic data includes: basic pipe network, land use and hydraulic facilities.

[0019] Optionally, the construction of a pipe network drainage evaluation index system for the city to be analyzed specifically includes:

[0020] Using the formula Determine the total overflow index OVR;

[0021] Using the formula Determine the total waterlogging index FVR;

[0022] Using the formula Determine the overflow distribution index ODR;

[0023] Using the formula Determine the waterlogging distribution index FDR;

[0024] Using the formula Determine the waterlogging pipeline ratio indicator FSR;

[0025] Using the formula Determine the FPR (Falling Waterlogging Potential Hazard Index);

[0026] in, is the overflow of node i, is the total runoff, is the amount of waterlogging at node i, It is the node where waterlogging occurs. , is the total number of all nodes, , is the water depth in pipe j at time t, is the top elevation of pipe j, is the surface elevation of pipeline j, n is the total number of nodes where overflow occurs, m is the total number of nodes where waterlogging occurs, Pipeline overload degree.

[0027] Optionally, the comprehensive drainage performance of the pipe network includes: the ratio of overflow water and internal waterlogging water to surface runoff water, the spatial distribution of the overflow volume of different overflow ports and the internal waterlogging volume of different sub-areas, the proportion of internal waterlogging pipe sections and the potential danger of overload.

[0028] According to the specific embodiments provided in this application, this application has the following technical effects:

[0029] This application provides an urban waterlogging analysis method that takes into account the spatiotemporal distribution characteristics of rainfall. By designing rainstorm scenarios and synthetic rainfall models, simulating the uncertainty of the spatiotemporal distribution of rainfall, constructing an urban pipe network drainage evaluation and waterlogging analysis method, coupling the uncertain spatiotemporal distribution structure of rainfall to the urban hydrological and hydrodynamic model, conducting rainfall spatiotemporal distribution response analysis, and improving the reliability of urban drainage capacity evaluation. Different spatiotemporal distribution scenarios of rainfall are constructed through the uncertain spatiotemporal distribution structure of rainfall, and the different spatiotemporal distribution scenarios of rainfall are combined with the urban hydrological and hydrodynamic model. Taking into account the uncertainty structure of the spatiotemporal distribution of rainfall, the comprehensiveness and predictability of pipe network evaluation, and other system states, waterlogging analysis is carried out based on multiple simulations. Key indicators are determined based on the constructed pipe network drainage evaluation index system, forming a set of urban waterlogging analysis methods that take into account the spatiotemporal distribution characteristics of rainfall. This application uses the value range of key indicators under the conditions of uncertain spatiotemporal distribution of rainfall to replace a single value to judge the weak links of urban waterlogging, thereby improving the adaptability of the analysis results in a changing environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 This is a flow chart of a method for analyzing urban waterlogging that considers the temporal and spatial distribution characteristics of rainfall in one embodiment of the present application;

[0032] Figure 2 Schematic diagram of the gridding of the city to be analyzed and the spatial movement of the rainstorm center (the horizontal and vertical coordinates refer to the spatial coordinate position, the unit is m);

[0033] Figure 3 This is a schematic diagram of the spatial distribution of rainfall contour lines in different rainstorm centers;

[0034] Figure 4 This is a spatial diagram of drainage capacity evaluation indicators under different rainstorm center scenarios (the vertical axis represents the value range, the horizontal axis represents the recurrence period, and y represents years). DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0036] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0037] In an exemplary embodiment, Figure 1 As shown, a method for analyzing urban waterlogging considering the temporal and spatial distribution characteristics of rainfall is provided, which includes the following S101 to S105.

[0038] S101: Constructing the uncertain spatial and temporal distribution structure of rainfall based on the designed rainstorm scenario and synthetic rainfall model of the city to be analyzed;

[0039] S101 specifically includes:

[0040] S11, determine the design rainstorm scenario using the design rainstorm formula for the city to be analyzed;

[0041] The design rainstorm formula is: ;

[0042] in, is the design rainstorm intensity (mm / h), is the rainfall duration (h), is the design return period (years), 、 、 、 The parameters are determined based on local historical data and storm design specifications.

[0043] S12, using the formula Determine the synthetic rainfall model; the synthetic rainfall model uses a two-dimensional Gaussian truncated distribution;

[0044] in, is the formula for spatially non-uniform rainfall intensity (mm / h), , is the design rainstorm intensity (mm / h) determined by the rainstorm intensity formula, D is the domain of the two-dimensional truncated Gaussian distribution, A is the basin area, , is the scaling function of the Gaussian distribution, ensuring that the integral of the distribution in the domain is 1, are the mean and variance of the Gaussian distribution, ( ) is the spatial coordinate of the rainstorm center, are the coordinates of any point in space, is the Gaussian distribution function.

[0045] S102: Based on the basic data of the city to be analyzed and the Storm Water Management Model (SWMM), an urban hydrological and hydrodynamic model is constructed with the uncertain spatial and temporal distribution structure of rainfall as input; the basic data includes but is not limited to: basic pipe network, land use, and hydraulic facilities.

[0046] The SWMM model can be divided into four components: external input data, surface runoff generation and confluence, underground pipe network confluence, and water quality treatment. After starting the model, SWMM loads external input data (such as rainfall data). This rainfall data is then fed into the subcatchments, accounting for evaporation, infiltration, and interception, generating surface runoff. This runoff then flows through nodes associated with the subcatchments (such as stormwater grates and manholes) and enters the underground pipe network. Within the underground pipe network, rainwater flows through pipes and confluence to outlets, ultimately discharging outside the system. Model results provide information on the flow process associated with the outlets. After constructing the SWMM model and validating its parameters using a measured rainstorm process, the uncertain temporal and spatial distribution of rainfall is incorporated as input.

[0047] S103, constructing a pipe network drainage evaluation index system for the city to be analyzed; the pipe network drainage evaluation index system includes: a total overflow index, a total internal waterlogging index, an overflow distribution index, an internal waterlogging distribution index, an internal waterlogging pipeline ratio index, and an internal waterlogging potential hazard index;

[0048] S103 specifically includes:

[0049] Using the formula Determine the total overflow index OVR;

[0050] Using the formula Determine the total waterlogging index FVR;

[0051] Using the formula Determine the overflow distribution index ODR;

[0052] Using the formula Determine the waterlogging distribution index FDR;

[0053] Using the formula Determine the waterlogging pipeline ratio indicator FSR;

[0054] Using the formula Determine the FPR (Falling Waterlogging Potential Hazard Index);

[0055] in, is the overflow of node i, is the total runoff, is the amount of waterlogging at node i, It is the node where waterlogging occurs. , is the total number of all nodes, , is the water depth in pipe j at time t, is the top elevation of pipe j, is the surface elevation of pipeline j, n is the total number of nodes where overflow occurs, m is the total number of nodes where waterlogging occurs, Pipeline overload degree.

[0056] S104: Determine the spatiotemporal distribution characteristics of waterlogging and overflow based on the urban hydrological and hydrodynamic model; and determine key indicators in the drainage network evaluation index system based on the spatiotemporal distribution characteristics of waterlogging and overflow.

[0057] By incorporating the spatiotemporal distribution characteristics of rainfall into the urban pipe network drainage capacity evaluation system, the impact of rainfall intensity, rainstorm center, etc. on the performance evaluation of the drainage system is taken into consideration. By constructing an uncertain spatiotemporal distribution structure of rainfall and an urban waterlogging overflow evaluation index system, and simulating urban hydrology and hydrodynamics based on the rainstorm and flood management model, key evaluation indicators are determined, thus achieving comprehensiveness, objectivity and adaptability in urban waterlogging analysis and drainage capacity evaluation.

[0058] S105: Analyze the value ranges of key indicators based on the uncertain spatiotemporal distribution structure of rainfall, and evaluate the comprehensive drainage performance of the city's pipe network based on the value ranges. The comprehensive drainage performance of the pipe network includes: the ratio of overflow water and waterlogging water to surface runoff water, the spatial distribution of overflow volume proportions at different overflow outlets and waterlogging proportions in different sub-areas, the proportion of waterlogging pipe sections, and the potential risk of overload.

[0059] Specifically, in the design rainstorm formula , , , .

[0060] There are 25×16=400 grid points in total for the rainstorm center, and the numbers are set as follows: 0, 1, 2, ..., 24 from left to right, and 0, 1, 2, ..., 15 from bottom to top. That is, the lower left corner is (0, 0) (marked by the blue cloud), and upwards are (0, 1), (0, 2), (0, 3) ..., and to the right are (1, 0), (2, 0), (3, 0), etc.

[0061] The key indicator system for pipe network drainage evaluation is shown in Table 1:

[0062] Table 1

[0063]

[0064] The following takes the city to be analyzed as an example of a real small watershed generalization to verify the applicability, rationality and effectiveness of the urban waterlogging analysis method that takes into account the temporal and spatial distribution characteristics of rainfall.

[0065] like Figure 2 As shown in Figure 1, the city to be analyzed is a real case study of Community A in a certain city. The study area belongs to the monsoon climate zone, and rainstorms and floods have obvious seasonality. Rainstorms occur mainly in the summer from June to September, accounting for about 80% of the annual rainfall. Among them, heavy rainstorms mainly occur from late July to early August, which puts tremendous pressure on urban flood control and drainage. The area of ​​this area is approximately 2.2 km 2 , of which the total length of the rainwater pipe network is about 25.4km.

[0066] In terms of temporal characteristics, the design rainstorm recurrence period is set to 50 years, the rainstorm lasts 24 hours, and the time step is 5 minutes. In terms of spatial characteristics, the rainstorm center is selected as the lower left corner, the center of the basin, and the upper right corner, respectively. The corresponding rainstorm center coordinates and model numbers are (0, 0), (12, 7), (24, 15), and 0, 77, 279. The spatial distribution of rainfall contour lines under these three scenarios is visualized, as shown in the figure below. Figure 3 (1) part of ~ Figure 3 The evaluation indexes of system drainage capacity under three scenarios are calculated, as shown in Table 2.

[0067] Table 2 Calculation results of drainage capacity evaluation indexes for different rainstorm centers

[0068]

[0069] In addition, the schematic diagram of the calculation results of the ODR and FDR evaluation indicators is as follows: Figure 3 As shown in parts (4) to (9) of the . The results show that when the rainstorm center is located in different geographical locations, some indicators have significant changes. Taking the waterlogging distribution index FDR as an example, when the rainstorm center is located in the lower left corner of the basin, the proportion of water in the corresponding sub-basin waterlogging increases significantly, indicating that this part is a weak link for waterlogging. The waterlogging pipeline proportion index FSR is the largest, and the waterlogging potential hazard index FPR is the smallest. Taking the overflow distribution index ODR as an example, when the rainstorm center is located in the lower left corner of the basin, the proportion of water in the corresponding regional overflow outlet reaches 12.3%. When the rainstorm center moves to the right, the overflow volume of the overflow outlet gradually decreases to 6.8%, which is half the amount. In addition, the overflow volume proportion of the overflow outlet in the lower right corner of the basin also gradually increases, from 17% to 23.1%. Therefore, with the change in the spatiotemporal distribution of rainfall, the spatial distribution of the waterlogging overflow risk area also changes accordingly.

[0070] Furthermore, combined with different design rainstorm recurrence periods (5-year, 10-year, 20-year, 30-year, and 50-year), the changes in drainage capacity indicators corresponding to the distribution of rainstorm centers in the entire basin were calculated. The results are as follows: Figure 4 As shown in the figure, with the increase in the design rainstorm return period, various indicators show a certain increase, while their range of variation also varies significantly. For example, the FSR (Federal Flood Pipeline Ratio) and the FPR (Federal Flood Potential Hazard) show a smaller range of variation under a 5-year return period scenario, but a larger range of variation under a 20-50 year return period scenario. Compared with the waterlogging risk indicators under a single scenario, changes in the center of the rainstorm have a greater impact on the calculated values ​​of the indicators. Compared with a single baseline scenario, evaluation results based on uncertain spatial and temporal distributions of rainfall are more conducive to identifying weak links and key indicators in drainage under specific scenarios, and are conducive to a comprehensive and integrated understanding of the drainage performance of the pipe network, and improving its predictability and adaptability.

[0071] Based on the analysis results of the above embodiments, the evaluation method proposed in the present invention can couple the uncertain spatiotemporal structure of rainfall with the urban waterlogging overflow evaluation index system, and comprehensively analyze the system's urban waterlogging situation and drainage performance under different rainstorm recurrence periods, rainstorm center locations and other scenarios, providing technical support for effectively improving the weak links of urban waterlogging and key drainage indicators.

[0072] This application comprehensively applies the uncertain spatial and temporal structure of rainfall and the waterlogging overflow evaluation index system to urban waterlogging analysis, with the following results:

[0073] 1. Comprehensively consider the impact of rainfall temporal and spatial characteristics on urban hydrological and hydrodynamic processes, and combine the designed rainstorm scenario with the synthetic rainfall model to construct the uncertain rainfall temporal and spatial distribution structure to enhance the comparability between input conditions and real scenarios;

[0074] 2. Based on the urban hydrological and hydrodynamic model, the calculation of key indicators of urban flooding overflow is combined with uncertain rainfall input, making the evaluation results of urban pipe network drainage capacity more comprehensive, objective, predictive and adaptable.

[0075] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0076] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0077] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0078] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0079] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0080] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for analyzing urban waterlogging that considers the temporal and spatial distribution characteristics of rainfall, characterized by: The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall includes: Constructing the uncertain spatial and temporal distribution structure of rainfall based on the designed rainstorm scenario and synthetic rainfall model of the city to be analyzed; Based on the basic data of the city to be analyzed and the storm flood management model, an urban hydrological and hydrodynamic model with the uncertain spatial and temporal distribution structure of rainfall as input is constructed; Constructing a drainage network evaluation index system for the city to be analyzed; the drainage network evaluation index system includes: a total overflow index, a total waterlogging index, an overflow distribution index, a waterlogging distribution index, a waterlogging pipeline ratio index, and a waterlogging potential hazard index; Determine the spatiotemporal distribution characteristics of waterlogging and overflow based on the urban hydrological and hydrodynamic model; and determine the key indicators in the drainage network evaluation index system based on the spatiotemporal distribution characteristics of waterlogging and overflow; The value ranges of key indicators are analyzed based on the uncertain spatiotemporal distribution structure of rainfall, and the comprehensive performance of the drainage network in the city to be analyzed is evaluated based on the value ranges.

2. The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall according to claim 1 is characterized in that: The construction of an uncertain rainfall spatiotemporal distribution structure based on the designed rainstorm scenario and synthetic rainfall model of the city to be analyzed specifically includes: Determine the design stormwater scenario using the design stormwater formula for the city to be analyzed; Using the formula Determine the synthetic rainfall model; in, is the formula for spatially non-uniform rainfall intensity, , is the design rainstorm intensity determined by the rainstorm intensity formula, D is the domain of the two-dimensional truncated Gaussian distribution, A is the basin area, , is the scaling function of the Gaussian distribution, ensuring that the integral of the distribution in the domain is 1, are the mean and variance of the Gaussian distribution, ( ) is the spatial coordinate of the rainstorm center, are the coordinates of any point in space, is the rainfall duration, is the Gaussian distribution function.

3. The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall according to claim 2 is characterized in that: The design rainstorm formula is: ; in, To design the rainstorm intensity, is the design return period, 、 、c、 As a parameter.

4. The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall according to claim 1 is characterized in that: The basic data include: basic pipe network, land use and hydraulic facilities.

5. The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall according to claim 1 is characterized in that: The construction of the waterlogging drainage evaluation index system for the city to be analyzed specifically includes: Using the formula Determine the total overflow index OVR; Using the formula Determine the total waterlogging index FVR; Using the formula Determine the overflow distribution index ODR; Using the formula Determine the waterlogging distribution index FDR; Using the formula Determine the waterlogging pipeline ratio indicator FSR; Using the formula Determine the FPR (Falling Waterlogging Potential Hazard Index); in, is the overflow of node i, is the total runoff, is the amount of waterlogging at node i, It is the node where waterlogging occurs. , is the total number of all nodes, , is the water depth in pipe j at time t, is the top elevation of pipe j, is the surface elevation of pipeline j, n is the total number of nodes where overflow occurs, m is the total number of nodes where waterlogging occurs, Pipeline overload degree.

6. The urban waterlogging analysis method considering the temporal and spatial distribution characteristics of rainfall according to claim 1 is characterized in that: The comprehensive drainage performance of the pipe network includes: the ratio of overflow water and internal waterlogging water to surface runoff water, the spatial distribution of the proportion of overflow volume at different overflow outlets and the proportion of internal waterlogging volume in different sub-areas, the proportion of internal waterlogging pipe sections and the potential danger of overload.

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