A method and system for monitoring urban drainage and flood control data

Abstract

The present invention discloses a method and system for monitoring urban drainage and flood prevention data, which specifically relates to the field of urban drainage technology, including S1, drainage and flood prevention area determination, determining the data in a target city as a target drainage and flood prevention area, and then dividing it into sub-areas according to equal time and equal area division methods, and numbering the sub-areas in the target drainage and flood prevention area in sequence as 1, 2, ..., i, ..., n according to equal time, and in sequence as 1, 2, ..., j, ..., m according to equal area; S2, drainage system data collection, acquiring the drainage system data in the target drainage and flood prevention area in real time, and transmitting it to the drainage system data processing step; the present invention simultaneously analyzes and judges the drainage system data and meteorological data, can smoothly integrate and analyze data from multiple different sources, ensure the comprehensiveness and depth of the monitoring data, and improve the overall monitoring effect.

Description

Technical Field

[0001] The present invention relates to the technical field of urban drainage, and more specifically, to a method and system for monitoring urban drainage and flood prevention data. Background Art

[0002] With the acceleration of urbanization, urban waterlogging is becoming more and more serious. The smoothness of the urban drainage system is directly related to the city’s flood control and drainage capacity, which can play a role in ensuring environmental safety, residents’ health, economic development, and flood control and resistance. Therefore, it is particularly important to develop a system that can monitor, warn and dispatch drainage and flood control resources in real time.

[0003] The traditional urban drainage system includes a data acquisition module, a data processing module, and a decision support module; the data acquisition module is used to collect real-time data of the urban drainage system; the data processing module processes and analyzes the collected data to establish an urban waterlogging risk prediction model; the decision support module predicts and analyzes the processed data to generate early warning information and dispatch instructions.

[0004] However, it still has some shortcomings in actual use, such as insufficient accuracy. The traditional urban drainage system has loopholes in data collection and only analyzes a single cause, which cannot fully and accurately reflect the operating status of the entire drainage system; poor real-time performance. The traditional urban drainage system only collects data information within a period of time and monitors the monitoring data in real time, and has limited processing capabilities. It is unable to quickly process and analyze a large amount of monitoring data in real time, resulting in poor real-time performance; incomplete data. The traditional monitoring system may lack effective data fusion technology and cannot integrate and analyze these multi-source data, making the monitoring data not comprehensive enough.

[0005] Therefore, there is an urgent need to provide a method and system for monitoring urban drainage and flood control data to solve the problems of insufficient accuracy, poor real-time performance, and incomplete data in the existing urban drainage system. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for monitoring urban drainage and flood control data, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0007] To achieve the above object, the present invention provides the following technical solution: a method for monitoring urban drainage and flood prevention data, comprising:

[0008] S1. Determine the drainage and flood control area. Determine the data in the target city as the target drainage and flood control area, and then divide it into sub-areas according to equal time and equal area division. The sub-areas in the target drainage and flood control area are numbered 1, 2, ..., i, ..., n in sequence according to equal time, and 1, 2, ..., j, ..., m in sequence according to equal area;

[0009] S2, drainage system data collection, real-time acquisition of drainage system data in the target drainage and flood control area, and transmission of the data to the drainage system data processing step;

[0010] S3, drainage system data processing, processing the drainage system data obtained in S2 to obtain the pipeline data influence coefficient, the pump station data influence coefficient and the inspection well data influence coefficient, and transmitting them to the comprehensive data analysis step;

[0011] S4, environmental data collection, real-time acquisition of environmental data in the target drainage and flood control area, and transmission of the data to the environmental data processing step;

[0012] S5, environmental data processing, processing the environmental data obtained in S4 to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmitting them to the comprehensive data analysis step;

[0013] S6, comprehensive data analysis, importing the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values ​​and water body data influence coefficient values ​​obtained in S3 and S5 into the waterlogging occurrence rationality index mathematical model, obtaining the waterlogging occurrence rationality index value, and transmitting it to the waterlogging assessment and judgment step;

[0014] S7, waterlogging assessment and judgment, comparing the waterlogging occurrence rationality index value obtained in S6 with the preset waterlogging occurrence rationality index value, calculating the difference between the waterlogging occurrence rationality index value and the preset waterlogging occurrence rationality index value, and obtaining a judgment result based on the difference;

[0015] S8, human-computer interaction, transmits the difference value, judgment result and data in the target drainage and flood prevention area obtained in S7 to the user information terminal.

[0016] Preferably, the drainage system data processing includes the steps of calculating the influence coefficient of pipeline data, the influence coefficient of pump station data and the influence coefficient of inspection well data; the environmental data processing step includes the steps of calculating the influence coefficient of meteorological data and the influence coefficient of water body data.

[0017] Preferably, the drainage system data includes pipeline data influencing parameters, pump station data influencing parameters and inspection well data influencing parameters;

[0018] The pipeline data influencing parameters include pipeline flow, denoted as Qp; pipeline water flow velocity, denoted as v; liquid level height in the pipeline, denoted as h; pipeline leakage rate, denoted as L; pump station data influencing parameters include pumping power of the pump station, denoted as P; pump station flow, denoted as Qb; pump station head, denoted as Hb; inspection well data influencing parameters include inspection well water level, denoted as Hw; inspection well blockage rate, denoted as D; inspection well flow, denoted as Qw.

[0019] Preferably, the pipeline data influence coefficient calculation step is used to import the pipeline data influence parameters into the pipeline data influence coefficient mathematical model to obtain the pipeline data influence coefficient value; the pump station data influence coefficient calculation step is used to import the pump station data influence parameters into the pump station data influence coefficient mathematical model to obtain the pump station data influence coefficient value; the inspection well data influence coefficient calculation step is used to import the inspection well data influence parameters into the inspection well data influence coefficient mathematical model to obtain the inspection well data influence coefficient value.

[0020] Preferably, the pipeline data influence coefficient mathematical model is specifically:

[0021] ,

[0022] The mathematical model of the pump station data influence coefficient is as follows:

[0023] ,

[0024] The mathematical model of the influence coefficient of inspection well data is as follows:

[0025] ,

[0026] where Qp (i，j) represents the pipeline flow rate of the jth area in the i-th time period, L (i，j) represents the pipeline leakage rate of the jth area in the i-th time period; v (i，j) represents the water flow velocity in the pipe of the jth area in the i-th time period, h (i，j) Indicates the liquid level height in the pipe of the jth area in the i-th time period; Qb (i，j) represents the pumping station flow rate of the jth area in the i-th time period, Pb (i，j) It represents the pumping power of the pumping station in the jth area in the i-th time period; represents the density of water; g represents the acceleration due to gravity; Hb (i，j) represents the pumping station head of the jth area in the i-th time period; Qw (i，j) represents the flow rate of the inspection well in the jth area in the i-th time period; D (i，j) Hw represents the blockage rate of the manhole in the jth area in the i-th time period; (i，j)It represents the water level of the inspection well in the jth area in the i-th time period.

[0027] Preferably, the environmental data includes meteorological data influencing parameters and water body data influencing parameters;

[0028] The meteorological data influencing parameters include rainfall, denoted as R; temperature, denoted as T; relative humidity, denoted as H; water body data influencing parameters include water body water level, denoted as Hh; groundwater level, denoted as Hu; water body flow, denoted as Qh; groundwater flow, denoted as Qu.

[0029] Preferably, the meteorological data influence coefficient calculation step is used to import the meteorological data influence parameters into the meteorological data influence coefficient mathematical model to obtain the meteorological data influence coefficient value; the water body data influence coefficient calculation step is used to import the water body data influence parameters into the water body data influence coefficient mathematical model to obtain the water body data influence coefficient value.

[0030] Preferably, the meteorological data influence coefficient mathematical model is specifically:

[0031] ,

[0032] The mathematical model of the water body data influence coefficient is as follows:

[0033] ,

[0034] Where T (i，j) represents the temperature of the jth area in the i-th time period; R (i，j) represents the rainfall in the jth area in the i-th time period; H (i，j) represents the relative humidity of the jth area in the i-th time period; T max represents the maximum permissible temperature for waterlogging, H max Indicates the maximum allowable relative humidity for waterlogging; Qh (i，j) represents the water flow rate of the jth area in the i-th time period; Qu (i，j) Hh represents the groundwater flow in the jth area in the i-th time period; (i，j) Hu represents the water level of the jth area in the i-th time period; (i，j) It represents the groundwater level of the jth area in the i-th time period.

[0035] Preferably, the mathematical model of the rationality index of waterlogging occurrence is specifically:

[0036] ,

[0037] in Indicates the influence coefficient value of pipeline data in the jth area; represents the value of the pump station data influence coefficient in the jth area; Indicates the value of the influence coefficient of the inspection well data in the jth area; Indicates the impact coefficient of meteorological data in the jth area; Represents the water body data influence coefficient value in the jth area.

[0038] Preferably, an urban drainage and flood control data monitoring system comprises:

[0039] Drainage and flood control area determination module: used to determine the data in the target city as the target drainage and flood control area, and then divide it into sub-areas according to equal time and equal area division methods, and number each sub-area in the target drainage and flood control area in sequence as 1, 2, ..., i, ..., n according to equal time, and 1, 2, ..., j, ..., m according to equal area;

[0040] Drainage system data acquisition module: used to obtain drainage system data in the target drainage and flood control area in real time and transmit it to the drainage system data processing module;

[0041] Drainage system data processing module: used to process the drainage system data obtained by the drainage system data acquisition module to obtain the pipeline data influence coefficient, pump station data influence coefficient and inspection well data influence coefficient, and transmit them to the comprehensive data analysis module;

[0042] Environmental data acquisition module: used to obtain environmental data in the target drainage and flood control area in real time and transmit it to the environmental data processing module;

[0043] Environmental data processing module: used to process the environmental data obtained by the environmental data acquisition module to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmit them to the comprehensive data analysis module;

[0044] Comprehensive data analysis module: used to import the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values ​​and water body data influence coefficient values ​​obtained in the drainage system data processing module and the environmental data processing module into the waterlogging occurrence rationality index mathematical model, obtain the waterlogging occurrence rationality index value, and transmit it to the waterlogging assessment and judgment module;

[0045] Waterlogging assessment and judgment module: compare the waterlogging occurrence rationality index value obtained by the comprehensive data analysis module with the preset waterlogging occurrence rationality index value, calculate the difference between the waterlogging occurrence rationality index value and the preset waterlogging occurrence rationality index value, and transmit the corresponding judgment result and the data in the target drainage and waterlogging prevention area to the human-computer interaction module according to the relationship between the difference value and the preset difference value;

[0046] Human-computer interaction module: used to transmit the difference value, judgment result and data in the target drainage and flood prevention area obtained by the flood disaster assessment and judgment module to the user information terminal.

[0047] Technical effects and advantages of the present invention:

[0048] The present invention collects drainage system data and meteorological data at the same time, judges the flood disaster situation from multiple factors, and comprehensively and accurately reflects the operation status of the entire drainage system;

[0049] The present invention can continuously collect and monitor comprehensive data information in real time, has powerful data processing capabilities, and can quickly process and analyze massive amounts of monitoring data in real time, thereby ensuring its excellent real-time performance;

[0050] The present invention analyzes and judges drainage system data and meteorological data at the same time, and can smoothly integrate and analyze data from multiple different sources, ensuring the comprehensiveness and depth of monitoring data and improving the overall monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0052] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] As attached Figure 1 The method for monitoring urban drainage and flood control data shown includes S1, determining the drainage and flood control area, S2, collecting drainage system data, S3, processing drainage system data, S4, collecting environmental data, S5, processing environmental data, S6, comprehensive data analysis, S7, evaluating and judging flood disasters, and S8, human-computer interaction.

[0055] S1. Determine the drainage and flood control area. Determine the data in the target city as the target drainage and flood control area. Then divide it into sub-areas according to equal time and equal area. Number the sub-areas in the target drainage and flood control area as 1, 2, ..., i, ..., n in sequence according to equal time, and as 1, 2, ..., j, ..., m in sequence according to equal area.

[0056] S2, drainage system data collection, real-time acquisition of drainage system data in the target drainage and flood control area, and transmission of the data to the drainage system data processing step.

[0057] In this embodiment, it should be specifically explained that the drainage system data includes pipeline data influencing parameters, pump station data influencing parameters and inspection well data influencing parameters.

[0058] In this embodiment, it is specifically necessary to explain that the pipeline data influencing parameters include pipeline flow, denoted as Qp; pipeline water flow velocity, denoted as v; liquid level height in the pipeline, denoted as h; pipeline leakage rate, denoted as L; pump station data influencing parameters include pumping power of the pump station, denoted as P; pump station flow, denoted as Qb; pump station head, denoted as Hb; inspection well data influencing parameters include inspection well water level, denoted as Hw; inspection well blockage rate, denoted as D; inspection well flow, denoted as Qw.

[0059] S3, drainage system data processing, the drainage system data obtained in S2 is processed to obtain the pipeline data influence coefficient, the pump station data influence coefficient and the inspection well data influence coefficient, and transmitted to the comprehensive data analysis step.

[0060] In this embodiment, it should be specifically explained that the drainage system data processing includes a pipeline data influence coefficient calculation step, a pump station data influence coefficient calculation step, and a manhole data influence coefficient calculation step.

[0061] In this embodiment, it is specifically necessary to explain that the pipeline data influence coefficient calculation step is used to import the pipeline data influence parameters into the pipeline data influence coefficient mathematical model to obtain the pipeline data influence coefficient value; the pump station data influence coefficient calculation step is used to import the pump station data influence parameters into the pump station data influence coefficient mathematical model to obtain the pump station data influence coefficient value; the inspection well data influence coefficient calculation step is used to import the inspection well data influence parameters into the inspection well data influence coefficient mathematical model to obtain the inspection well data influence coefficient value.

[0062] In this embodiment, it should be specifically explained that the mathematical model of the pipeline data influence coefficient is specifically:

[0063] ,

[0064] The mathematical model of the pump station data influence coefficient is as follows:

[0065] ,

[0066] The mathematical model of the influence coefficient of inspection well data is as follows:

[0067] ,

[0068] where Qp(i，j) represents the pipeline flow rate of the jth area in the i-th time period, L (i，j) represents the pipeline leakage rate of the jth area in the i-th time period; v (i，j) represents the water flow velocity in the pipe of the jth area in the i-th time period, h (i，j) Indicates the liquid level height in the pipe of the jth area in the i-th time period; Qb (i，j) represents the pumping station flow rate of the jth area in the i-th time period, Pb (i，j) It represents the pumping power of the pumping station in the jth area in the i-th time period; represents the density of water; g represents the acceleration due to gravity; Hb (i，j) represents the pumping station head of the jth area in the i-th time period; Qw (i，j) represents the flow rate of the inspection well in the jth area in the i-th time period; D (i，j) Hw represents the blockage rate of the manhole in the jth area in the i-th time period; (i，j) It represents the water level of the inspection well in the jth area in the i-th time period.

[0069] S4, environmental data collection, real-time acquisition of environmental data in the target drainage and flood control area, and transmission to the environmental data processing step.

[0070] In this embodiment, it should be specifically explained that the environmental data includes meteorological data influencing parameters and water body data influencing parameters.

[0071] In this embodiment, it should be specifically explained that the meteorological data influencing parameters include rainfall, denoted as R; temperature, denoted as T; relative humidity, denoted as H; water body data influencing parameters include water body water level, denoted as Hh; groundwater level, denoted as Hu; water body flow, denoted as Qh; groundwater flow, denoted as Qu.

[0072] S5, environmental data processing, processing the environmental data obtained in S4 to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmitting them to the comprehensive data analysis step.

[0073] In this embodiment, it should be specifically explained that the environmental data processing step includes a meteorological data influence coefficient calculation step and a water body data influence coefficient calculation step.

[0074] In this embodiment, it should be specifically explained that the meteorological data influence coefficient calculation step is used to import the meteorological data influence parameters into the meteorological data influence coefficient mathematical model to obtain the meteorological data influence coefficient value; the water body data influence coefficient calculation step is used to import the water body data influence parameters into the water body data influence coefficient mathematical model to obtain the water body data influence coefficient value.

[0075] In this embodiment, it should be specifically explained that the meteorological data influence coefficient mathematical model is specifically:

[0076] ,

[0077] The mathematical model of the water body data influence coefficient is as follows:

[0078] ,

[0079] Where T (i，j) represents the temperature of the jth area in the i-th time period; R (i，j) represents the rainfall in the jth area in the i-th time period; H (i，j) represents the relative humidity of the jth area in the i-th time period; T max represents the maximum permissible temperature for waterlogging, H max Indicates the maximum allowable relative humidity for waterlogging; Qh (i，j) represents the water flow rate of the jth area in the i-th time period; Qu (i，j) Hh represents the groundwater flow in the jth area in the i-th time period; (i，j) Hu represents the water level of the jth area in the i-th time period; (i，j) It represents the groundwater level of the jth area in the i-th time period.

[0080] S6. Comprehensive data analysis: import the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values, and water body data influence coefficient values ​​obtained in S3 and S5 into the waterlogging occurrence rationality index mathematical model to obtain the waterlogging occurrence rationality index value, and transmit it to the waterlogging assessment and judgment step.

[0081] In this embodiment, it should be specifically explained that the mathematical model of the rationality index of waterlogging occurrence is specifically:

[0082] ,

[0083] in Indicates the influence coefficient value of pipeline data in the jth area; represents the value of the pump station data influence coefficient in the jth area; Indicates the value of the influence coefficient of the inspection well data in the jth area; Indicates the impact coefficient of meteorological data in the jth area; Represents the water body data influence coefficient value in the jth area.

[0084] S7. Waterlogging assessment and judgment: compare the waterlogging occurrence rationality index value obtained in S6 with the preset waterlogging occurrence rationality index value, calculate the difference between the waterlogging occurrence rationality index value and the preset waterlogging occurrence rationality index value, and obtain the judgment result based on the difference.

[0085] In this embodiment, it should be specifically explained that the preset flood occurrence rationality index value is the minimum value of the historical flood occurrence rationality index values; the preset difference value is the minimum value of the difference between the historical flood occurrence rationality index value and the preset flood occurrence rationality index value.

[0086] In this embodiment, it is specifically necessary to explain that the judgment result obtained based on the difference value is: when the difference value is less than the preset difference value, the judgment result is that waterlogging is likely to occur, and the judgment result and the data in the target drainage and flood prevention area are transmitted to the human-computer interaction step; when the difference value is greater than the preset difference value, the judgment result is that waterlogging is not likely to occur, and the judgment result and the data in the target drainage and flood prevention area are transmitted to the human-computer interaction step.

[0087] S8, human-computer interaction, transmits the difference value, judgment result and data in the target drainage and flood prevention area obtained in S7 to the user information terminal.

[0088] As attached Figure 2 As shown, it is an overall system schematic diagram of an urban drainage and flood control data monitoring system, which specifically includes: a drainage and flood control area determination module, a drainage system data acquisition module, a drainage system data processing module, an environmental data acquisition module, an environmental data processing module, a comprehensive data analysis module, a flood disaster assessment and judgment module, and a human-computer interaction module.

[0089] The drainage and flood control area determination module is used to determine the data within the target city as the target drainage and flood control area, and then divide it into sub-areas according to equal time and equal area division methods, and number the sub-areas in the target drainage and flood control area in sequence as 1, 2, ..., i, ..., n according to equal time, and 1, 2, ..., j, ..., m according to equal area.

[0090] The drainage system data acquisition module is used to obtain the drainage system data in the target drainage and flood control area in real time and transmit it to the drainage system data processing module.

[0091] The drainage system data processing module is used to process the drainage system data obtained by the drainage system data acquisition module to obtain the pipeline data influence coefficient, the pump station data influence coefficient and the inspection well data influence coefficient, and transmit them to the comprehensive data analysis module.

[0092] The environmental data acquisition module is used to obtain the environmental data in the target drainage and flood control area in real time and transmit it to the environmental data processing module.

[0093] The environmental data processing module is used to process the environmental data obtained by the environmental data acquisition module to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmit them to the comprehensive data analysis module.

[0094] The comprehensive data analysis module is used to import the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values ​​and water body data influence coefficient values ​​obtained in the drainage system data processing module and the environmental data processing module into the mathematical model of the rationality index of waterlogging occurrence, obtain the rationality index value of waterlogging occurrence, and transmit it to the waterlogging assessment and judgment module.

[0095] The waterlogging assessment and judgment module compares the waterlogging rationality index value obtained by the comprehensive data analysis module with the preset waterlogging rationality index value, calculates the difference between the waterlogging rationality index value and the preset waterlogging rationality index value, and transmits the corresponding judgment results and data in the target drainage and waterlogging prevention area to the human-computer interaction module according to the relationship between the difference value and the preset difference value.

[0096] The human-computer interaction module is used to transmit the difference value, judgment result and data in the target drainage and flood prevention area obtained by the flood disaster assessment and judgment module to the user information terminal.

[0097] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0098] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for monitoring urban drainage and flood control data, characterized in that: include: S1. Determine the drainage and flood control area. Determine the data in the target city as the target drainage and flood control area, and then divide it into sub-areas according to equal time and equal area division. The sub-areas in the target drainage and flood control area are numbered 1, 2, ..., i, ..., n in sequence according to equal time, and 1, 2, ..., j, ..., m in sequence according to equal area; S2, drainage system data collection, real-time acquisition of drainage system data in the target drainage and flood control area, and transmission of the data to the drainage system data processing step; The drainage system data includes pipeline data influencing parameters, pump station data influencing parameters and inspection well data influencing parameters; The pipeline data influencing parameters include pipeline flow, recorded as Qp; pipeline water flow velocity, recorded as v; pipeline liquid level height, recorded as h; pipeline leakage rate, recorded as L; pump station data influencing parameters include pump station pumping power, recorded as P; pump station flow, recorded as Qb; pump station head, recorded as Hb; inspection well data influencing parameters include inspection well water level, recorded as Hw; inspection well blockage rate, recorded as D; inspection well flow, recorded as Qw; S3, drainage system data processing, processing the drainage system data obtained in S2 to obtain the pipeline data influence coefficient, the pump station data influence coefficient and the inspection well data influence coefficient, and transmitting them to the comprehensive data analysis step; The drainage system data processing includes the steps of calculating the influence coefficient of pipeline data, the influence coefficient of pump station data and the influence coefficient of inspection well data; The pipeline data influence coefficient calculation step is used to import the pipeline data influence parameters into the pipeline data influence coefficient mathematical model to obtain the pipeline data influence coefficient value; the pump station data influence coefficient calculation step is used to import the pump station data influence parameters into the pump station data influence coefficient mathematical model to obtain the pump station data influence coefficient value; the inspection well data influence coefficient calculation step is used to import the inspection well data influence parameters into the inspection well data influence coefficient mathematical model to obtain the inspection well data influence coefficient value; The mathematical model of the pipeline data influence coefficient is specifically: ， The mathematical model of the pump station data influence coefficient is as follows: ， The mathematical model of the influence coefficient of inspection well data is as follows: ， where Qp (i，j) represents the pipeline flow rate of the jth area in the i-th time period, L (i，j) represents the pipeline leakage rate of the jth area in the i-th time period; v (i，j) represents the water flow velocity in the pipe of the jth area in the i-th time period, h (i，j) Indicates the liquid level height in the pipe of the jth area in the i-th time period; Qb (i，j) represents the pumping station flow rate of the jth area in the i-th time period, Pb (i，j) It represents the pumping power of the pumping station in the jth area in the i-th time period; represents the density of water; g represents the acceleration due to gravity; Hb (i，j) represents the pumping station head of the jth area in the i-th time period; Qw (i，j) It represents the flow rate of the inspection well in the jth area in the i-th time period; D (i，j) Hw represents the blockage rate of the manhole in the jth area in the i-th time period; (i，j) It represents the water level of the inspection well in the jth area in the i-th time period; S4, environmental data collection, real-time acquisition of environmental data in the target drainage and flood control area, and transmission of the data to the environmental data processing step; The environmental data include meteorological data influencing parameters and water body data influencing parameters; The meteorological data influencing parameters include rainfall, recorded as R; temperature, recorded as T; relative humidity, recorded as H; water body data influencing parameters include water body water level, recorded as Hh; groundwater level, recorded as Hu; water body flow, recorded as Qh; groundwater flow, recorded as Qu; S5, environmental data processing, processing the environmental data obtained in S4 to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmitting them to the comprehensive data analysis step; The environmental data processing step includes a meteorological data influence coefficient calculation step and a water body data influence coefficient calculation step; The meteorological data influence coefficient calculation step is used to import the meteorological data influence parameters into the meteorological data influence coefficient mathematical model to obtain the meteorological data influence coefficient value; the water body data influence coefficient calculation step is used to import the water body data influence parameters into the water body data influence coefficient mathematical model to obtain the water body data influence coefficient value; The mathematical model of the meteorological data influence coefficient is specifically: ， The mathematical model of the water body data influence coefficient is as follows: ， Where T (i，j) represents the temperature of the jth area in the i-th time period; R (i，j) represents the rainfall in the jth area in the i-th time period; H (i，j) It represents the relative humidity of the jth area in the i-th time period; T max represents the maximum permissible temperature for waterlogging, H max Indicates the maximum allowable relative humidity for waterlogging; Qh (i，j) represents the water flow rate of the jth area in the i-th time period; Qu (i，j) Hh represents the groundwater flow in the jth area in the i-th time period; (i，j) Hu represents the water level of the jth area in the i-th time period; (i，j) It represents the groundwater level of the jth area in the i-th time period; S6, comprehensive data analysis, importing the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values ​​and water body data influence coefficient values ​​obtained in S3 and S5 into the waterlogging occurrence rationality index mathematical model, obtaining the waterlogging occurrence rationality index value, and transmitting it to the waterlogging assessment and judgment step; The mathematical model of the rationality index of waterlogging occurrence is specifically as follows: ， in Indicates the influence coefficient value of pipeline data in the jth area; represents the value of the pump station data influence coefficient in the jth area; Indicates the value of the influence coefficient of the inspection well data in the jth area; Indicates the impact coefficient of meteorological data in the jth area; Indicates the water body data influence coefficient value in the jth area; S7, waterlogging assessment and judgment, comparing the waterlogging occurrence rationality index value obtained in S6 with the preset waterlogging occurrence rationality index value, calculating the difference between the waterlogging occurrence rationality index value and the preset waterlogging occurrence rationality index value, and obtaining a judgment result based on the difference; S8, human-computer interaction, transmits the difference value, judgment result and data in the target drainage and flood prevention area obtained in S7 to the user information terminal.

2. An urban drainage and flood control data monitoring system, used to implement the urban drainage and flood control data monitoring method of claim 1, characterized in that: include: Drainage and flood control area determination module: used to determine the data in the target city as the target drainage and flood control area, and then divide it into sub-areas according to equal time and equal area division methods, and number each sub-area in the target drainage and flood control area in sequence as 1, 2, ..., i, ..., n according to equal time, and 1, 2, ..., j, ..., m according to equal area; Drainage system data acquisition module: used to obtain drainage system data in the target drainage and flood control area in real time and transmit it to the drainage system data processing module; Drainage system data processing module: used to process the drainage system data obtained by the drainage system data acquisition module to obtain the pipeline data influence coefficient, pump station data influence coefficient and inspection well data influence coefficient, and transmit them to the comprehensive data analysis module; Environmental data acquisition module: used to obtain environmental data in the target drainage and flood control area in real time and transmit it to the environmental data processing module; Environmental data processing module: used to process the environmental data obtained by the environmental data acquisition module to obtain the meteorological data influence coefficient and the water body data influence coefficient, and transmit them to the comprehensive data analysis module; Comprehensive data analysis module: used to import the pipeline data influence coefficient values, pump station data influence coefficient values, inspection well data influence coefficient values, meteorological data influence coefficient values ​​and water body data influence coefficient values ​​obtained in the drainage system data processing module and the environmental data processing module into the waterlogging occurrence rationality index mathematical model, obtain the waterlogging occurrence rationality index value, and transmit it to the waterlogging assessment and judgment module; Waterlogging assessment and judgment module: compare the waterlogging occurrence rationality index value obtained by the comprehensive data analysis module with the preset waterlogging occurrence rationality index value, calculate the difference between the waterlogging occurrence rationality index value and the preset waterlogging occurrence rationality index value, and transmit the corresponding judgment result and the data in the target drainage and waterlogging prevention area to the human-computer interaction module according to the relationship between the difference value and the preset difference value; Human-computer interaction module: used to transmit the difference value, judgment result and data in the target drainage and flood prevention area obtained by the flood disaster assessment and judgment module to the user information terminal.

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