Water supply pipeline working condition stochastic simulation method based on pavement elevation and surface rainfall

Abstract

The invention relates to the technical field of pipe network working condition simulation, in particular to a water supply pipeline working condition stochastic simulation method based on pavement elevation and areal rainfall, which comprises the following steps of: establishing an urban pipe network model, and assigning a random value to each water supply pipe section in the pipe network model through a stochastic simulation method; and then calculating a pavement elevation correction coefficient and a surface rainfall correction coefficient of each water supply pipe section on the basis of the pavement elevation and the surface rainfall, correcting a random value by using the pavement elevation correction coefficient and the surface rainfall correction coefficient, calculating a cumulative probability according to a correction result, and judging the working condition of the water supply pipeline through the cumulative probability. According to the method, working condition changes under the conditions of extreme weather, natural disasters and the like can be better simulated, the layout of the water supply pipe network can be adjusted according to the simulation result, redundant pipe sections are increased or pipeline connection is optimized, and the emergency water supply capacity of the pipe network is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline network working condition assessment, and particularly relates to a method and system for randomly simulating the working conditions of water supply pipelines based on road surface elevation and surface rainfall. Background Art

[0002] Urban water supply pipelines are a crucial part of urban infrastructure and play a fundamental role in the normal operation of the city and the quality of life of residents. Specifically, urban water supply pipelines can ensure the daily living needs of residents, support urban economic activities, maintain public health and safety, enhance emergency response capabilities, promote urban sustainable development, improve urban disaster resistance capabilities, promote environmental protection and optimize water resource management, and can enhance the urban image and residents' happiness.

[0003] The stability and reliability of urban water supply pipe networks are the key to ensuring the water supply of urban residents and meeting the development of urban industries. Especially in extreme situations, such as when urban water supply pipelines are damaged, urban water sources are polluted, and the city encounters extreme weather, it is very important whether the performance of urban water supply pipelines can still meet the water demand of urban residents and industries when facing different working conditions.

[0004] At present, for the simulation of water supply pipeline working conditions, conventional methods include physical model method, traditional computational fluid dynamics (CFD) method, network model method, and empirical model method. However, these methods all have certain limitations, such as high computational complexity, poor real-time performance, and insufficient adaptability to dynamic changes. Summary of the Invention

[0005] In view of the defects and problems existing in the current simulation technology of water supply pipe network working conditions, the present invention provides a method for randomly simulating the working conditions of water supply pipelines based on road surface elevation and surface rainfall.

[0006] The present invention provides a method for randomly simulating the working conditions of water supply pipelines based on road surface elevation and surface rainfall, including the following steps:

[0007] S1. Construct an urban water supply pipe network model, count and record M water-using nodes and N water supply pipe segments in the water supply pipe network model, and assign a random value X n to each water supply pipe segment, where n is the water supply pipe segment number, n = 1, 2,..., N,

[0008] X n = μ + σ·Φ -1 (x n )

[0009] In the formula: Φ -1 represents the inverse function of the cumulative distribution function of the standard normal distribution;

[0010] S2. Calculate the road surface elevation h of the water supply pipeline section, and calculate the road surface elevation correction coefficient η of each water supply pipeline section according to the elevation data of the water supply pipeline section. n n ;

[0011] S3. Divide the area into grids to obtain the surface rainfall of each grid; match each water supply pipeline section with the corresponding grid surface rainfall to obtain the surface rainfall p of each water supply pipeline section, and calculate the surface rainfall correction coefficient of each water supply pipeline section according to the surface rainfall data of each water supply pipeline section. n

[0012] S4. According to the road surface elevation correction coefficient η of the water supply pipeline section n and the surface rainfall correction coefficient correct the normal distribution random value X corresponding to each water supply pipeline section n to obtain the corrected random value XL. n ;

[0013]

[0014] S5. Calculate the cumulative probability of the normal distribution.

[0015]

[0016] In the formula: Φ is the cumulative function of the standard normal distribution; μ is the population mean, and σ 2 is the population standard deviation;

[0017] S6. Judge the working condition of the water supply pipeline according to the cumulative probability of the normal distribution. If the cumulative probability of the normal distribution is less than 5% or greater than 95%, the corresponding water supply pipeline section cannot operate normally; if the cumulative probability is between 5% and 95%, the water supply pipeline section can operate normally.

[0018] For the above-mentioned random simulation method of the working condition of the water supply pipeline based on the road surface elevation and surface rainfall, step S1 specifically includes the following steps:

[0019] (1) Construct a city water supply network model, assuming that there are M water-using nodes and N water supply pipeline sections in the city water supply network model;

[0020] (2) Randomly generate N random numbers between 0 and 1, denoted as x1, x2, …… x n , …… x N , and each random number corresponds to a water supply pipeline section;

[0021] (3) Randomly generate a set of data X:N(μ, σ 2 ) based on the normal distribution, where μ is the population mean and σ 2 is the population standard deviation;

[0022] (4) Use the random number in (2) as the probability. Based on the standard normal distribution, calculate the normal distribution random value corresponding to each random number according to the population mean and population standard deviation, denoted as X. n Each normal distribution random value corresponds to a water supply pipeline segment.

[0023] For the above-mentioned random simulation method of water supply pipeline working conditions based on road surface elevation and surface rainfall, step S2 specifically includes the following steps:

[0024] (1) Obtain the elevation data of each water use node in the research area. Calculate the elevation of the water supply pipeline segment between two water use nodes according to the elevation data of the two water use nodes. The elevation of the water supply pipeline segment is the average of the road surface elevations of the water use nodes at both ends of the water supply pipeline segment.

[0025] (2) Calculate the road surface elevation correction coefficient η of each water supply pipeline segment according to the elevation data of each water supply pipeline segment. n ,

[0026]

[0027] In the formula: represents the average of the road surface elevation of the water supply pipeline segment; h max represents the maximum value of the road surface elevation in the water supply pipeline segment; h min represents the minimum value of the road surface elevation in the water supply pipeline segment.

[0028] For the above-mentioned random simulation method of water supply pipeline working conditions based on road surface elevation and surface rainfall, the road surface elevation data is obtained through a geographic information system or map software in step (1).

[0029] For the above-mentioned random simulation method of water supply pipeline working conditions based on road surface elevation and surface rainfall, step S3 specifically includes the following steps:

[0030] (1) Divide the area into S grid blocks in sequence according to the longitude and latitude range of the area.

[0031] (2) Obtain the surface rainfall data of different grids in the area. Match each water supply pipeline segment with its corresponding grid surface rainfall, denoted as p1, p2,..., p n , ……p N , where p n represents the surface rainfall of the nth water supply pipeline segment.

[0032] (3) Calculate the surface rainfall correction coefficient φ of each water supply pipeline segment according to the surface rainfall data of the water supply pipeline segment. n ,

[0033]

[0034] In the formula: represents the average value of the areal rainfall of the water supply pipeline section; p max represents the maximum value of the areal rainfall in the water supply pipeline section; p min represents the minimum value of the areal rainfall in the water supply pipeline section.

[0035] In the above method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall, when performing grid division in step (1), the grid width is determined according to the size of the area and does not exceed half of the longitude and latitude span of the area.

[0036] In the above method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall, in step (2), the areal rainfall data of different grids in the target area is obtained through remote sensing technology.

[0037] In the above method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall, in step (2), the matching principle for each water supply pipeline section to be matched with its corresponding grid areal rainfall is that the areal rainfall of all water supply pipeline sections included within the grid range is the areal rainfall of this grid.

[0038] The present invention also provides a system for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall, including a water supply pipe network model establishment module for establishing a water supply pipe network simulation model; a data acquisition module for obtaining the road surface elevation data and areal rainfall data of the water supply pipeline section; a random simulation module for randomly simulating the operating conditions of the water supply pipeline according to the road surface elevation data and areal rainfall data of the water supply pipeline section; and a result analysis module for evaluating the operating conditions of the water supply pipeline according to the simulation situation of the random simulation module.

[0039] Compared with the prior art, the beneficial effects of the present invention are:

[0040] 1. The method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall provided by the present invention does not require complex calculation formulas. By randomly generating normal distribution numbers and calculating their cumulative probability values, the determination of the operating conditions of the water supply pipeline can be achieved.

[0041] 2. The method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall provided by the present invention can more accurately reflect the actual situation. This method takes into account the possible influences of road surface elevation and areal rainfall, converts the uncertain road surface elevation data and areal rainfall data into definite correction coefficients, and reduces the influence of the external environment on the results.

[0042] 3. The method for randomly simulating the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall provided by the present invention can improve the adaptability of the model. By simulating different operating condition changes, this method can perform multi-scenario tests on the pipe network design, which helps to better cope with complex and changeable operating conditions.

[0043] 4. The present invention simulates the operating conditions of water supply pipelines based on road surface elevation and surface rainfall, which can better simulate the changes in operating conditions under extreme weather, natural disasters and other conditions. It can also simulate different water supply pipe networks and adjust the layout of the water supply pipe network according to the simulation results, add redundant pipe sections or optimize pipe connections, and improve the emergency water supply capacity of the pipe network. Description of the Drawings

[0044] Figure 1 It is a schematic diagram of a tree - shaped urban water supply pipe network.

[0045] Figure 2 It is a schematic diagram of a ring - shaped urban water supply pipe network.

[0046] Figure 3 It is a schematic diagram of the grid division of the research area. Detailed Embodiments

[0047] Aiming at the defects and problems existing in the current simulation technology of water supply pipe network operating conditions, the present invention provides a stochastic simulation method for water supply pipeline operating conditions based on road surface elevation and surface rainfall. This method establishes a mathematical model of the water supply pipeline, conducts stochastic simulations for different situations, and realizes the simulation of the pipe network operating conditions by correcting based on road surface elevation and surface rainfall. The influence of road surface elevation on the pipe network is mainly reflected in the following aspects: First, the road surface elevation affects the hydrodynamics of water flow, specifically manifested as directly affecting the water flow pressure and flow direction of the pipeline. Especially in the design and hydraulic calculation of water supply pipelines, the water flow usually depends on gravity. Therefore, the elevation difference will affect the flow velocity and pressure distribution of the water flow, especially in areas with large topographic undulations. Second, the road surface elevation affects the design and optimization of the pipe network, specifically reflected in the selection of pumps, pipeline layout, and the design of water towers and water storage facilities. The ground elevation is a very crucial parameter, and different elevation differences will affect the water supply pressure, and appropriate design is required to ensure the stable operation of the system. Finally, the road surface elevation affects the calculation of water pressure, specifically manifested as if the change in road surface elevation is ignored, it may lead to inaccurate estimation of the water pressure of the pipe network, thereby affecting the reliability and efficiency of water supply.

[0048] The influence of surface rainfall on the pipe network is mainly reflected in the following aspects: First, in terms of simulating water source supply, surface rainfall will directly affect the rainwater collection system and the ability to supplement water supply. When simulating the urban water supply pipe network, the inflow of rainwater may become part of the groundwater recharge or affect the water source reserve of the water supply system; Second, in terms of flood control and drainage design, surface rainfall can predict the pressure fluctuations or impact load values of water pipes during heavy rain or rainstorms; Finally, in terms of water quality and water volume prediction, the precipitation will affect the pollution load of the water body, thereby affecting the water quality of the water supply.

[0049] The present invention is based on two indicators, namely road surface elevation and areal rainfall, and respectively corrects them through a stochastic simulation method. Without complex calculation formulas, by randomly generating normal distribution numbers and calculating their cumulative probability values, the condition determination of the water supply pipeline can be realized. The main contents are as follows.

[0050] Embodiment 1: This embodiment provides a stochastic simulation method for the condition of a water supply pipeline based on road surface elevation and areal rainfall. By comprehensively considering the geographical environment and meteorological conditions, this method realizes the multi-dimensional simulation of the operation state of the water supply network, thereby improving the reliability and safety of the water supply network. The main contents are as follows.

[0051] Step 1: Construct a city water supply network model, count and record M water-using nodes and N water supply pipeline segments in the water supply network model, and assign a normal distribution random value X to each water supply pipeline segment n ; specifically:

[0052] (1) Construct a city water supply network model. Assume that there are M water-using nodes in the water supply network model and N water supply pipeline segments in total; among them, it is set that a water supply pipeline segment is formed between two adjacent water-using nodes. For a tree-shaped city water supply network, the number of water supply pipeline segments is equal to the number of water-using nodes minus 1, that is, N = M - 1. As Figure 1 shown, there are 5 water-using nodes and 4 water supply pipeline segments between two adjacent water-using nodes, which conforms to the above relationship. For a loop-shaped city water supply network, the number of water supply pipeline segments is usually greater than the number of water-using nodes, that is, N > M. As Figure 2 shown, there are 14 water-using nodes and 19 water supply pipeline segments between two adjacent water-using nodes, which conforms to the above relationship.

[0053] (2) Generate random numbers: Randomly generate a set of random numbers between 0 and 1, denoted as x1, x2, …… x n , …… x N , and each random number corresponds to a water supply pipeline segment;

[0054] (3) Based on the normal distribution, randomly generate a set of data X: N(μ, σ 2 ), where μ is the population mean and σ 2 is the population standard deviation; when μ = 0 and σ 2 = 1, it is denoted as X: N(0, 1), which is called the standard normal distribution;

[0055] (4) Take the random numbers x1, x2, …… x n , …… x N generated in (2) as probabilities, and based on the standard normal distribution, calculate the normal distribution random value corresponding to each random number according to the population mean μ and the population standard deviation σ 2 , denoted as X1, X2, …… X n, ……X N , each normally distributed random value corresponds to a water supply pipe section

[0056] X n = μ + σ·Φ -1 (x n )

[0057] In the formula: Φ -1 represents the inverse function of the cumulative distribution function of the standard normal distribution

[0058] Step 2. Calculate the road surface elevation correction coefficient η of each water supply pipe section n ; specifically:

[0059] (1) Obtain the elevation of the water use nodes: During the random simulation, with the help of map software or geographic information system, obtain the elevation data of each water use node in the research area

[0060] (2) Calculate the elevation of the water supply pipe section: Take the average of the elevations of the water use nodes at both ends of the water supply pipe section as the elevation of the road surface where the water supply pipe section is located, denoted as h n ;

[0061] (3) Calculate the correction coefficient: According to the elevation data of the water supply pipe section, calculate the road surface elevation correction coefficient η of each water supply pipe section respectively n ,

[0062]

[0063] In the formula: represents the average of the road surface elevation of the water supply pipe section represents the average of the elevations of all water supply pipe sections; h max represents the maximum value of the road surface elevation among all water supply pipe sections; h min represents the minimum value of the road surface elevation among all water supply pipe sections

[0064] Step 3. Calculate the surface rainfall correction coefficient of each water supply pipe section Specifically:

[0065] (1) According to the longitude and latitude range of the region, divide the research area into grids in sequence. The unit grid width can be determined by technicians in combination with the size of the research area, not exceeding 1 / 2 of the longitude and latitude span of the research area; when dividing the grids, it is necessary to ensure that the divided grids can completely cover all water supply pipe sections in the research area to ensure the accuracy and comprehensiveness of the simulation results

[0066] (2) Assume that after dividing the research area into grids, a total of S grids can be obtained. With the help of remote sensing technology, obtain the surface rainfall data of different grids in the target area

[0067] (3) Matching water supply pipe segments: Match each water supply pipe segment with its corresponding grid surface rainfall. The specific matching rule is as follows: For all water supply pipe segments contained within a certain grid range, their surface rainfall amounts are all the surface rainfall data of that grid, denoted as p1, p2, ……, p n , …… p N , where p n represents the surface rainfall amount of the nth water supply pipe segment.

[0068] (4) Calculating the correction coefficient: Calculate the surface rainfall correction coefficient φ for each water supply pipe segment based on the surface rainfall data of the water supply pipe segment n ,

[0069]

[0070] In the formula: represents the average value of the surface rainfall amount of the water supply pipe segment; p max represents the maximum value of the surface rainfall amount in the water supply pipe segment; p min represents the minimum value of the surface rainfall amount in the water supply pipe segment.

[0071] Step Four: According to the road surface elevation correction coefficient η of the water supply pipe segment n and the surface rainfall correction coefficient correct the normal distribution random value X corresponding to each water supply pipe segment n to obtain the corrected random value XL n ;

[0072]

[0073] Step Five: Calculate the cumulative probability of the normal distribution

[0074]

[0075] In the formula: Φ is the cumulative function of the standard normal distribution; μ is the population mean, σ 2 is the population standard deviation;

[0076] Step Six: In the constructed model, there are two situations for the working conditions of the water supply pipe segments, namely, the water supply pipe segments are working normally or cannot work normally; judge the working conditions of the water supply pipeline according to the cumulative probability of the normal distribution. If the cumulative probability of the normal distribution is less than 5% or greater than 95%, the corresponding water supply pipe segment cannot operate normally; if the cumulative probability is between 5% and 95%, the water supply pipe segment can operate normally.

[0077] Through the above operation steps, various different water supply network situations can be obtained. According to different situations, the water supply pipe segments that cannot work properly are closed, and then the operation processes of different water supply networks are simulated. Using the random simulation method of water supply pipeline working conditions based on road surface elevation and surface rainfall, various different water supply pipe segment working conditions can be obtained. These working conditions mainly refer to the situation where some water supply pipe segments in the water supply network cannot work properly. Considering from three aspects: network pressure, pipeline flow rate, and node water supply demand satisfaction, different water supply network situations are analyzed, and then the design scheme is optimized, and the water supply network is transformed or upgraded. Specifically, considering from the aspect of network pressure, if a certain water supply pipe segment cannot work properly, it will affect the fluidity of water supply and the pressure distribution of the network. The water supply pipe segment that cannot work properly will break the balance of maintaining the network water pressure by each water supply pipe segment, resulting in a local pressure drop or pressure fluctuation in the network. Considering from the aspect of pipeline flow rate, if a certain water supply pipe segment cannot work properly, it may lead to a reduction or interruption of the flow rate in that part. Considering from the aspect of node water supply demand satisfaction, combining the previous two aspects, if a certain water supply pipe segment cannot work properly, it will lead to insufficient water consumption at the node and water shortage.

[0078] Generally speaking, the random simulation method of water supply pipeline working conditions based on road surface elevation and surface rainfall simulates and analyzes the operation conditions of water supply networks with various different water supply pipe segments that cannot work properly, and improves the urban water supply network system and optimizes the urban water supply network design from three aspects: network pressure, pipeline flow rate, and node water supply demand satisfaction.

[0079] When the water supply pipe segments are damaged due to extreme weather or natural disasters and cannot work properly, the method of the present invention can also better simulate the changes in working conditions under conditions such as extreme weather and natural disasters. When heavy rain or continuous precipitation causes an increase in urban surface rainfall, it will lead to the overload operation of the urban drainage system and excessive network pressure. In addition, when the precipitation is large, rainwater seeps into the urban water supply system, increasing the water pressure of the urban water supply pipe segments and then causing damage, affecting the normal operation of the urban water supply system. Natural disasters mainly change the elevation where the urban water supply pipe segments are located. This change will affect the flow direction and speed of the water flow, and there may be situations such as urban road waterlogging, which will further increase the pressure of the urban underground water supply pipe segments, resulting in the rupture of the urban water supply pipe segments and their inability to work properly. Since it is impossible to artificially predict which urban water supply pipe segments will be damaged by natural disasters or extreme weather and the degree of damage, the normal distribution value of random numbers is calculated using the normal distribution, and then corrected using the elevation and surface rainfall. After calculation, different cumulative probabilities are obtained, and these probability values are used to simulate which water supply pipe segments are damaged and cannot work properly due to the changes in surface rainfall and elevation under conditions such as extreme weather and natural disasters.

[0080] For example, in case of emergency such as damage or blockage of the water supply pipeline, corresponding emergency measures should be formulated in advance, and the emergency response ability should be improved through drills and other means; different water supply pipe networks can be better simulated, and according to the simulation results, the layout of the water supply pipe network can be adjusted, redundant pipe sections can be added or pipe connections can be optimized to enhance the emergency water supply capacity of the pipe network. For example, standby pipelines can be set or water supply nodes can be added in important areas to ensure that when a certain pipe section fails, other pipe sections can carry sufficient water flow.

[0081] The above are only the preferred embodiments of the present invention and do not limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A random simulation method for the operating conditions of water supply pipelines based on road surface elevation and areal rainfall, characterized in that: It includes the following steps: S1. Build a model of the urban water supply network, count and record M water-using nodes and N water supply pipeline segments in the water supply network model, and assign a random value X to each water supply pipeline segment n ; S2. Calculate the road surface elevation h of the water supply pipeline section n , and calculate the road surface elevation correction coefficient η of each water supply pipeline section according to the road surface elevation of the water supply pipeline section n ; S3. Divide the area into grids and obtain the surface rainfall of each grid; match each water supply pipe section with the corresponding grid surface rainfall to obtain the surface rainfall p of each water supply pipe section n , and calculate the surface rainfall correction coefficient of each water supply pipe section according to the surface rainfall data of each water supply pipe section S4. Modify the normal distribution random value X corresponding to each water supply pipe segment according to the road surface elevation correction coefficient η of the water supply pipe segment n and the surface rainfall correction coefficient to obtain the corrected random value XL n for the normal distribution random value X corresponding to each water supply pipe segment n ; S5. Calculate the cumulative probability of the normal distribution. where: Φ is the cumulative function of the standard normal distribution; μ is the population mean, and σ 2 is the population standard deviation; S6. Judge the working condition of the water supply pipeline according to the cumulative probability of the normal distribution. If the cumulative probability of the normal distribution is less than 5% or greater than 95%, the corresponding water supply pipe section cannot operate normally; if the cumulative probability is between 5% and 95%, the water supply pipe section can operate normally.

2. The random simulation method for the working conditions of a water supply pipeline based on road surface elevation and areal rainfall according to claim 1, wherein: Step S1 specifically includes the following steps: (1) Construct a urban water supply network model, assuming that there are M water consumption nodes and N water supply pipe sections in the urban water supply network model. (2) Randomly generate N random numbers between 0 and 1, denoted as x1, x2, …… x n , …… x N , and each random number corresponds to a water supply pipe segment; (3) Use the random number in (2) as the probability. Based on the standard normal distribution, calculate the normal distribution random value corresponding to each random number according to the population mean and population standard deviation, denoted as X n , and each normal distribution random value corresponds to a water supply pipeline segment X n = μ + σ·Φ -1 (x n ) where: Φ -1 represents the inverse function of the cumulative distribution function of the standard normal distribution.

3. The random simulation method for the working conditions of a water supply pipeline based on road surface elevation and surface rainfall amount according to claim 2, characterized in that: The urban water supply network described in step S1 includes a tree-shaped urban water supply network and a loop-shaped urban water supply network.

4. The random simulation method for the working conditions of a water supply pipeline based on road surface elevation and areal rainfall according to claim 1, characterized in that: Step S2 specifically includes the following steps: (1) Obtain the elevation data of each water consumption node in the research area, and calculate the road surface elevation of the water supply pipe section between two water consumption nodes according to the elevation data of the two water consumption nodes. The elevation of the water supply pipe section is the average value of the road surface elevations of the two water consumption nodes at both ends of the water supply pipe section. (2) Calculate the road surface elevation correction coefficient η for each water supply pipe section respectively according to the elevation data of each water supply pipe section. n , In the formula: represents the average value of the road surface elevation of the water supply pipe section; h max represents the maximum value of the road surface elevation in the water supply pipe section; h min represents the minimum value of the road surface elevation in the water supply pipe section.

5. The random simulation method for the working conditions of water supply pipelines based on road surface elevation and areal rainfall according to claim 4, wherein: In step (1), the road surface elevation data is obtained through a geographic information system or map software.

6. The random simulation method for the operating conditions of a water supply pipeline based on road surface elevation and surface rainfall amount according to claim 1, wherein: Step S3 specifically includes the following steps: (1) Divide the area into S grids in sequence according to the longitude and latitude range of the area. (2) Obtain the areal rainfall data of different grids within the area, and match each water supply pipe segment with its corresponding grid areal rainfall, denoted as p1, p2, ……, p n , ……p N , where p n represents the areal rainfall of the nth water supply pipe segment; (3) Calculate the areal rainfall correction coefficient φ for each water supply pipe section based on the areal rainfall data of the water supply pipe sections n , In the formula: represents the average value of the cross-sectional rainfall of the water supply pipe section; p max represents the maximum value of the cross-sectional rainfall in the water supply pipe section; p min represents the minimum value of the cross-sectional rainfall in the water supply pipe section.

7. The random simulation method for the operating conditions of a water supply pipeline based on road surface elevation and surface rainfall amount according to claim 6, characterized in that: When performing grid division in step (1), the grid width is determined according to the size of the area and does not exceed half of the longitude and latitude span of the area.

8. The random simulation method for the operating conditions of a water supply pipeline based on road surface elevation and surface rainfall amount according to claim 6, characterized in that: In step (2), the surface rainfall data of different grids in the target area is obtained through remote sensing technology.

9. The random simulation method for the operating conditions of a water supply pipeline based on road surface elevation and areal rainfall according to claim 6, characterized in that: The matching principle for each water supply pipe section to match the corresponding grid surface rainfall in step (2) is that the surface rainfall of all water supply pipe sections included in the grid range is the surface rainfall of this grid.

10. A random simulation system for the working conditions of water supply pipelines based on road surface elevation and surface rainfall, characterized in that: It includes: A water supply network model establishment module, which is used to establish a water supply network simulation model. A data acquisition module, which is used to obtain the road surface elevation data and surface rainfall data of the water supply pipe section. A random simulation module, which is used to perform random simulation on the working condition of the water supply pipeline according to the road surface elevation data and surface rainfall data of the water supply pipe section. A result analysis module, which is used to evaluate the working condition of the water supply pipeline according to the simulation situation of the random simulation module. ​

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