Accumulated water early warning method and system based on urban inland inundation simulation positioning

Abstract

The invention relates to the technical field of disaster early warning, in particular to an accumulated water early warning method and system based on urban inland inundation simulation positioning. The method comprises the following steps: acquiring a regional pipe network parameter set, analyzing the regional pipe network parameter set, and constructing a drainage pipe network model; acquiring a terrain parameter set and a key facility parameter set, analyzing the terrain parameter set and the key facility parameter set, and constructing a regional basic model; acquiring a meteorological parameter set, simulating the ponding development situation according to the regional basic model based on the meteorological parameter set and the drainage pipe network model, and determining a multi-dimensional risk information set; and based on the regional basic model, according to the multi-dimensional risk information set, determining a target pushing user and corresponding early warning pushing information, and pushing the early warning pushing information to the target pushing user. The method can accurately reflect the real-time comprehensive influence of the accumulated water under the multi-dimensional complex factors in the city, and effectively improves the accuracy, real-time performance and pertinence of the accumulated water early warning process.

Description

Technical Field

[0001] The present application relates to the field of disaster warning technology, and in particular to a method and system for early warning of waterlogging based on urban waterlogging simulation and positioning. Background Art

[0002] With the rapid advancement of urbanization and the frequent occurrence of extreme weather events, especially the increase in heavy rainfall, the urban drainage system is facing tremendous pressure, resulting in an increased frequency of urban flooding, which brings huge challenges to citizens' lives, infrastructure and urban management.

[0003] Traditional urban waterlogging warning technology usually relies on single-dimensional meteorological data, such as rainfall, rainfall intensity, and rainfall duration, to predict waterlogging risks. It is difficult to reflect the comprehensive impact of waterlogging under multi-dimensional and complex factors in the city, resulting in problems such as excessive data granularity, low warning real-time performance, and weak target targeting in the waterlogging warning process. Summary of the invention

[0004] The present application provides a waterlogging early warning method and system based on urban waterlogging simulation and positioning to solve the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a waterlogging early warning method based on urban waterlogging simulation positioning, the method comprising: Acquire a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; acquire a terrain parameter set and a key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model; acquire a meteorological parameter set, and based on the meteorological parameter set and the drainage pipe network model, simulate the development trend of waterlogging according to the regional basic model, and thereby determine a multidimensional risk information set; based on the regional basic model, determine the target push user and the corresponding warning push information according to the multidimensional risk information set, and push the warning push information to the target push user.

[0006] Through this solution, the regional pipe network parameter set, terrain parameter set and key facility parameter set are analyzed, and the drainage pipe network model and regional basic model are constructed to provide scientific data support for evaluating the risks brought about by the dynamic development of waterlogging. Based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, the dynamic waterlogging development trend formed by the dynamic precipitation affected by the drainage pipe network model on the regional basic model is simulated. In this way, the multidimensional risks brought about by the development of waterlogging are analyzed, and a multidimensional risk information set is obtained, which accurately reflects the real-time comprehensive impact of waterlogging under multidimensional and complex factors in the city. On this basis, combined with the regional basic model, the target push users and the corresponding warning push information are determined, and the warning push information is pushed to the target push users, which significantly improves the target pertinence of the waterlogging warning information.

[0007] Optionally, the pipe network parameter set includes drainage well data and pump station data, and the analyzing the regional pipe network parameter set to construct the drainage pipe network model includes: According to the drainage well data, the drainage well position, drainage well diameter, drainage well vertical depth and drainage path length corresponding to each drainage well are extracted; according to the drainage well diameter, the drainage well vertical depth and the drainage path length, a self-drainage capacity evaluation model of each drainage well is constructed, and the self-drainage capacity of each drainage well under a specified fluid velocity is determined thereby; according to the pump station data, the pump station position, pump station efficiency, total pump power and total water head of each pump station are extracted; the pump station data and the drainage well data are analyzed to determine the flow path length and flow path diameter between each pump station and different drainage wells connected thereto; based on the pump station efficiency and the total pump power, the pump station regulation capacity of each pump station for each drainage well connected thereto under a specified fluid velocity is determined according to the flow path length and the flow path diameter; the sum of the self-drainage capacity and the pump station regulation capacity is taken as the drainage capacity of the corresponding drainage well, a drainage network directed graph is constructed according to the drainage well position, the pump station position and the drainage capacity, and the drainage network directed graph is taken as the drainage network model.

[0008] Through this scheme, according to the drainage well diameter, vertical depth and drainage path length corresponding to the drainage well, a self-drainage capacity evaluation model is constructed to evaluate the self-drainage capacity of each drainage well. At the same time, based on the pump station efficiency and total pump power, according to the flow path length and flow path diameter, the pump station regulation capacity of each pump station for each drainage well connected to it is evaluated. On this basis, the drainage capacity of the drainage well is comprehensively evaluated, and a drainage network directed graph is constructed according to the drainage well location, pump station location and drainage capacity. The drainage network directed graph is used as the drainage network model to achieve highly abstract data processing of the urban drainage network. While scientifically evaluating the drainage capacity of the urban drainage network, the corresponding data structure is used to improve the dynamic expansion capability of the drainage network model to ensure the real-time nature of the subsequent waterlogging status analysis process.

[0009] Optionally, a self-drainage capacity evaluation model of each drainage well is constructed according to the drainage well diameter, the vertical depth of the drainage well and the drainage path length, and the self-drainage capacity of each drainage well at a specified fluid velocity is determined based on this model, which is specifically the following formula: ; in, For the The self-drainage capacity of a drainage well, For the The diameter of the drainage well of the drainage well, For the The fluid velocity in the drainage well, is the friction coefficient of the preset path, For the The length of the drainage path of the drainage well, is the acceleration due to gravity, For the The vertical depth of the drainage well of a drainage well.

[0010] Through this scheme, mathematical analysis methods are used, according to the diameter of the drainage well, the vertical depth of the drainage well and the length of the drainage path, and through mathematical language, a self-drainage capacity evaluation model is constructed to describe the influence of the above factors on the drainage capacity of the drainage well itself. The self-drainage capacity of each drainage well is scientifically quantified according to the self-drainage capacity evaluation model, so as to accurately measure the drainage capacity of the drainage well under the influence of its own design structure, and provide a solid data foundation for the subsequent analysis of the actual drainage capacity of the drainage well.

[0011] Optionally, based on the pump station efficiency and the total pump power, the pump station regulation capacity of each pump station for each drainage well connected thereto at a specified fluid velocity is determined according to the flow path length and the flow path diameter, specifically as follows: ; in, For the The pump station is connected to the The pump station regulation capacity of the drainage wells, is the pumping station efficiency, is the total pump power, is the total water head of the pumping station, is the friction coefficient of the preset path, For the Pumping station to The length of the flow path between the drainage wells, For the Pumping station to The velocity of the fluid in the flow path between the drainage wells, No. Pumping station to The flow path diameter between the drainage wells.

[0012] Through this scheme, mathematical analysis methods are used, based on the pump station efficiency and total pump power, according to the flow path length and flow path diameter, and mathematical language is used to clarify the influence of the above parameters on the regulating capacity of the pump station, so as to quantify the pump station regulating capacity of each drainage well connected to it at a specified fluid velocity, and then clarify the influence of the pump station on the drainage capacity of the drainage wells connected to it, further improving the accuracy and scientificity of the actual drainage capacity analysis process of the drainage wells.

[0013] Optionally, the terrain parameter set includes terrain elevation data, the key facility parameter set includes facility location data, facility type data, facility structure data and facility coverage area data, and the step of analyzing the terrain parameter set and the key facility parameter set to construct a regional basic model includes: According to the terrain elevation data and the facility location data, the relative terrain height of the location of each key facility is determined; based on the facility type data, the facility coverage area data is analyzed to determine the redundancy index and facility importance level of each key facility; the facility structure data is analyzed to determine the facility waterproof index of each key facility; according to the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index, the water accumulation sensitivity of each key facility is determined; according to the facility location data and the water accumulation sensitivity, each key facility is labeled with sensitivity; the terrain elevation data and the facility location data after labeling are uniformly spatially mapped to construct the regional basic model.

[0014] Through this plan, targeted analysis is conducted on the sensitivity of different types of key facilities to waterlogging at their locations based on relative terrain height, redundancy index, facility importance level, facility structural data and facility waterproof index, so as to scientifically reflect the sensitivity of different key facilities to waterlogging, provide a scientific basis for the subsequent quantification of multi-dimensional risks caused by waterlogging, and perform unified spatial mapping processing on the terrain elevation data and facility location data after annotation, build a regional basic model, avoid the misalignment deviation between terrain data and key data, and improve the accuracy and data consistency of the regional basic model.

[0015] Optionally, the water accumulation sensitivity of each key facility is determined according to the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index, specifically as the following formula: ; in, is the water accumulation sensitivity, is the importance level of the facility, is the preset magnification index, is the waterproof index of the facility, is the preset adjustment coefficient, is the redundancy index, is the preset redundancy influence coefficient, is the relative terrain height, is the preset decay index.

[0016] Through this plan, mathematical analysis methods are used to accurately quantify the water accumulation sensitivity of key facilities based on relative terrain height, redundancy index, facility importance level, facility structural data and facility waterproof index through clear mathematical relationships, thereby improving the scientificity and comprehensiveness of the water accumulation sensitivity analysis process, and thus improving the accuracy of the subsequent water accumulation risk analysis process based on water accumulation sensitivity.

[0017] Optionally, the meteorological parameter set includes real-time rainfall, rainfall change information, water collection information and flow rate information. Based on the meteorological parameter set and the drainage network model, according to the regional basic model, the development trend of waterlogging is simulated, and a multidimensional risk information set is determined based on this, including: Based on the flow rate information and the drainage network model, the real-time drainage capacity of each drainage well is determined; based on the water catchment information, the water catchment area of ​​each drainage well is extracted; based on the regional basic model, the surface elevation of the well point of each drainage well is determined; based on the real-time rainfall, the real-time drainage capacity and the water catchment area, the real-time runoff corresponding to each drainage well is determined, so as to determine the total runoff; based on the real-time rainfall, the total runoff, the real-time drainage capacity and the well point surface elevation, a water level change assessment model is constructed to assess the real-time waterlogging level; based on the water level change assessment model and the rainfall change information, the real-time waterlogging level is updated according to the water flow dynamics equation; based on the regional basic model, the real-time waterlogging level is analyzed to determine the waterlogging risk information corresponding to different key facilities, so as to determine the multi-dimensional risk information set.

[0018] Through this solution, based on the meteorological parameter set, according to the drainage network model and the regional basic model, under dynamic precipitation changes, the drainage network model and the regional basic model are combined to jointly influence the development trend of waterlogging, build a water level change assessment model, and evaluate the real-time waterlogging level in the area. At the same time, combined with the water flow dynamics equation, the real-time waterlogging level is dynamically updated to track the real-time waterlogging level changes. This is used as the dynamic data basis for determining the corresponding waterlogging risk information of different key facilities, so as to construct a multi-dimensional risk information set, which significantly improves the accuracy and real-time performance of multi-dimensional risk judgment.

[0019] Optionally, the water level change assessment model is constructed according to the real-time rainfall, the total runoff, the real-time drainage capacity and the surface elevation of the well point, which is specifically the following formula: ; in, is the real-time accumulated water level, is the total runoff volume, is the real-time rainfall, is the preset time step, For the The real-time drainage capacity of the drainage wells, is the indicator function, For the The surface elevation of the well point of a drainage well; the hydrodynamic equation is specifically the following formula: ; in, is the total runoff volume, is the runoff velocity vector, is the acceleration due to gravity, is the real-time accumulated water level, is the terrain elevation gradient.

[0020] Through this plan, mathematical analysis methods are used to construct a water level change assessment model based on real-time rainfall, total runoff, real-time drainage capacity and well surface elevation through clear mathematical relationships to achieve the assessment of real-time waterlogging levels. In combination with the water flow dynamics equation, the real-time waterlogging level can be dynamically updated to provide scientific support for the determination of the real-time waterlogging level, improve the accuracy of the judgment of the real-time waterlogging level, and thus improve the accuracy of multi-dimensional risk judgment based on the real-time waterlogging level.

[0021] Optionally, the real-time flooding water level is analyzed based on the regional basic model to determine the flooding risk information corresponding to different key facilities, thereby determining the multi-dimensional risk information set, including: According to the regional basic model, several key facilities located in the waterlogging area are determined; based on the real-time waterlogging water level and according to the waterlogging sensitivity corresponding to the several key facilities, the real-time waterlogging risk corresponding to each key facility is determined; according to the real-time waterlogging risk corresponding to each key facility and the facility coverage area data, the waterlogging risk information corresponding to the key facilities is constructed to determine the multi-dimensional risk information set.

[0022] Through this solution, based on the real-time water level, the key facilities affected by the current waterlogging status are screened, and combined with the corresponding waterlogging sensitivity of the key facilities, the real-time waterlogging risk of the key facilities is evaluated, and the facility coverage area data corresponding to the key facilities are further integrated to obtain the waterlogging risk information corresponding to the key facilities. Based on this, a multi-dimensional risk information set is constructed to assist in the precise delineation of different risk impact ranges, and further assist in determining different target users within different risk impact ranges, thereby improving the pertinence and accuracy of the push of waterlogging warning information.

[0023] In a second aspect, the present application provides a waterlogging early warning system based on urban waterlogging simulation positioning, the system comprising: The pipe network analysis module is used to obtain the regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; the regional analysis module is used to obtain the terrain parameter set and the key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model; the risk analysis module is used to obtain the meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, simulate the development trend of waterlogging according to the regional basic model, and determine the multidimensional risk information set accordingly; the early warning module is used to determine the target push user and the corresponding early warning push information based on the regional basic model and the multidimensional risk information set, and push the early warning push information to the target push user. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flow chart of a waterlogging early warning method based on urban waterlogging simulation positioning provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a waterlogging early warning system based on urban waterlogging simulation and positioning provided in one embodiment of the present application; Figure 4 This is a diagram of the operation interface of a waterlogging warning system based on urban waterlogging simulation and positioning provided in one embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0028] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0029] Traditional urban waterlogging warning technologies usually rely on single-dimensional meteorological models, which are difficult to reflect the comprehensive impact of waterlogging under multi-dimensional and complex factors in the city. As a result, the waterlogging warning process has problems such as excessive data granularity, low warning real-time performance, and weak target targeting.

[0030] Based on this, the present application provides a waterlogging warning method and system based on urban waterlogging simulation and positioning. The regional pipe network parameter set, terrain parameter set and key facility parameter set are analyzed to construct a drainage pipe network model and a regional basic model to provide scientific data support for assessing the risks brought about by the dynamic development of waterlogging. Based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, the dynamic precipitation is simulated on the regional basic model. The dynamic waterlogging development trend formed after being affected by the drainage pipe network model, the multidimensional risks brought about by the waterlogging development process are analyzed to obtain a multidimensional risk information set, which accurately reflects the real-time comprehensive impact of waterlogging under multidimensional and complex factors in the city. On this basis, combined with the regional basic model, the target push user and the corresponding warning push information are determined, and the warning push information is pushed to the target push user, which significantly improves the target pertinence of the waterlogging warning information.

[0031] Figure 1 A schematic diagram of an application scenario provided by this application. In the process of urban waterlogging warning, the method provided by this application is applied to accurately reflect the real-time comprehensive impact of waterlogging under multi-dimensional and complex factors in the city, and effectively improve the accuracy, real-time and pertinence of the waterlogging warning process.

[0032] Specifically, the method of the present application is applied to any server, which communicates with the municipal management department, the local remote sensing system, the key facility management department and the local meteorological department respectively. The server obtains and analyzes the regional pipe network parameter set provided by the municipal management department, the terrain parameter set provided by the local remote sensing system and the key facility parameter set provided by the key facility management department, and constructs a drainage pipe network model and a regional basic model to provide scientific data support for evaluating the risks brought about by the dynamic development of waterlogging. Based on the meteorological parameter set provided by the local meteorological department, according to the drainage pipe network model and the regional basic model, the dynamic waterlogging development trend formed by the dynamic precipitation on the regional basic model after being affected by the drainage pipe network model is simulated, so as to analyze the multidimensional risks brought about by the development of waterlogging, and obtain a multidimensional risk information set, which accurately reflects the real-time comprehensive impact of waterlogging under multidimensional and complex factors in the city. On this basis, combined with the regional basic model, the target push user and the corresponding warning push information are determined, and the warning push information is pushed to the target push user, which significantly improves the target pertinence of the waterlogging warning information.

[0033] For specific implementation methods, please refer to the following embodiments.

[0034] Figure 2 This is a flow chart of a waterlogging early warning method based on urban waterlogging simulation positioning provided by an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Obtain a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model.

[0035] The regional pipe network parameter set may be a set of drainage pipe network parameters within the urban waterlogging area to be monitored, and may include geometric data, pipe diameter data, etc. The regional pipe network parameter set may be provided by the municipal management department.

[0036] The drainage network model can be a mathematical model used to characterize the characteristics of the drainage network in a region.

[0037] Specifically, in the process of urban waterlogging warning, quickly and accurately analyzing the waterlogging status of various areas in the city is a necessary prerequisite for improving the real-time and accuracy of waterlogging warning. In the process of analyzing the waterlogging status, correctly understanding the structure and performance of the urban drainage system is the basis for subsequent analysis. Since the urban drainage pipe network system is widely distributed and has a complex structure, and with the development of urbanization and the implementation of pipe network maintenance work, the urban drainage pipe network system will often undergo local changes. Therefore, according to the regional pipe network parameter set, a data structure with a high degree of data abstraction and easy to expand, such as a directed graph, is used to construct a mathematical model corresponding to the urban drainage pipe network, and a drainage pipe network model is obtained, which can provide real-time and refined data support for subsequent waterlogging status analysis, and can be dynamically updated when local changes occur in the drainage pipe network system, ensuring that the subsequent waterlogging status analysis process can quickly obtain accurate drainage pipe network information.

[0038] S202: Obtain a terrain parameter set and a key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model.

[0039] The terrain parameter set may be a set of terrain parameters within an urban area that is the subject of waterlogging monitoring, and may include terrain elevation information of various areas of the city. The terrain parameter set may be provided by a local remote sensing system.

[0040] The key facility parameter set may be a set of public facility parameters that have a key impact on the production and life of residents in an urban area, and the key facility parameter set may be provided by the key facility management department.

[0041] The regional basic model can be a mathematical model used to characterize the terrain and key facilities characteristics within the urban area.

[0042] Specifically, the development trend of waterlogging in cities is directly affected by the terrain characteristics of different areas in the city, in addition to being affected by the drainage network. Changes in the slope of the terrain in the city directly determine the flow and convergence direction of precipitation on the urban surface, which in turn affects the distribution of waterlogging in various areas of the city. By combining the analysis of urban terrain characteristics and drainage network characteristics, it is possible to track changes in the development trend of waterlogging in various areas of the city. However, the impact of waterlogging on the area in which it is located cannot be unilaterally evaluated from the perspective of waterlogging volume and waterlogging time. The production and life of residents in modern cities depend on key public facilities distributed throughout the city, such as power facilities, water supply facilities, etc. If these facilities are damaged by waterlogging during urban waterlogging, even if the waterlogging volume and waterlogging time do not reach the current urban standards for waterlogging grade classification, the impact it brings cannot be ignored. In addition, the risk of damage to different types of key facilities in the city caused by waterlogging will cause dynamic changes in the target objects and warning ranges in the waterlogging warning process. The division of target objects and warning ranges is no longer simply determined by the state of waterlogging diffusion. Instead, as the waterlogging situation develops, the number of key facilities facing the risk of waterlogging damage increases. The impact range of waterlogging caused by the damage to key facilities will be centered on the location of the key facilities and spread outward with the corresponding specific responsible range. At the same time, the target objects affected by it will change in this process. For example, if power facilities are damaged by waterlogging, the corresponding warning range should be expanded to the power supply range responsible for the power facility, and the warning target objects should also be included in the warning target objects based on the residents in the waterlogging diffusion area. By introducing key facilities in the process of waterlogging status analysis, the judgment of waterlogging impact is more comprehensive and humane, and it has important guiding significance for the accurate delineation of warning targets and warning ranges in the subsequent waterlogging warning process. Through mathematical analysis, the terrain parameter set and the key facility parameter set are analyzed, and the regional basic model is constructed, which can provide scientific data support for the above analysis process.

[0043] S203, obtaining a meteorological parameter set, simulating the development trend of waterlogging based on the meteorological parameter set and the drainage network model and the regional basic model, and thereby determining a multidimensional risk information set.

[0044] The meteorological parameter set may be a set of local meteorological parameters in an urban area, and the meteorological parameter set may be provided by a local meteorological system. The development trend of waterlogging may be a diffusion trend of waterlogging in the urban area.

[0045] The multidimensional risk information set may be a collection of multidimensional risk information caused by waterlogging in the urban area where the waterlogging is located.

[0046] Specifically, the development trend of waterlogging in cities is directly affected by meteorological changes. After constructing the drainage network model and the regional basic model, the meteorological change information corresponding to the meteorological parameter set is introduced, and further mathematical analysis methods are used to accurately simulate the dynamic waterlogging development trend formed by the dynamic precipitation brought by the meteorological change information being affected by the drainage network model on the regional basic model. With the changes in the dynamic waterlogging development trend, the impact risks of waterlogging on different types of key facilities in the urban area where it is located change accordingly, and the specific risks of different types of key facilities affected by waterlogging are in different dimensions. Therefore, the risk changes brought about by the dynamic waterlogging development trend show a multi-dimensional development trend. According to the simulated waterlogging development trend and combined with the parameters of various types of key facilities in the regional basic model, mathematical analysis methods are used to quantify the multi-dimensional risks brought about by the waterlogging development process, and then a multi-dimensional risk information set is obtained to support the subsequent targeted technical early warning process.

[0047] S204: Based on the regional basic model and the multi-dimensional risk information set, determine the target push user and the corresponding warning push information, and push the warning push information to the target push user.

[0048] The target push users may be users who need to be reminded of the multi-dimensional risks caused by waterlogging in the current urban area. The warning push information may be targeted push information that needs to be warned to the target users for different risks caused by waterlogging.

[0049] Specifically, after determining the multidimensional risk information set, the scope of impact of different risks is delineated based on the regional basic model and the corresponding key facility parameters according to the different risks reflected in the multidimensional risk information set. At the same time, corresponding warning information is extracted from the preset information template database according to the type of different risks. According to the scope affected by different risks, the target users within the scope are determined through cellular network positioning technology, and the corresponding warning information is pushed to the data terminal owned by the target user, such as a mobile phone, so that the target user can clearly understand the risks caused by waterlogging he is currently facing.

[0050] Through this solution, the regional pipe network parameter set, terrain parameter set and key facility parameter set are analyzed, and the drainage pipe network model and regional basic model are constructed to provide scientific data support for evaluating the risks brought about by the dynamic development of waterlogging. Based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, the dynamic waterlogging development trend formed by the dynamic precipitation affected by the drainage pipe network model on the regional basic model is simulated. In this way, the multidimensional risks brought about by the development of waterlogging are analyzed, and a multidimensional risk information set is obtained, which accurately reflects the real-time comprehensive impact of waterlogging under multidimensional and complex factors in the city. On this basis, combined with the regional basic model, the target push users and the corresponding warning push information are determined, and the warning push information is pushed to the target push users, which significantly improves the target pertinence of the waterlogging warning information.

[0051] In some embodiments, based on the drainage well data, the drainage well position, drainage well diameter, drainage well vertical depth and drainage path length corresponding to each drainage well are extracted; based on the drainage well diameter, drainage well vertical depth and drainage path length, a self-drainage capacity evaluation model of each drainage well is constructed, and the self-drainage capacity of each drainage well at a specified fluid velocity is determined thereby; based on the pump station data, the pump station position, pump station efficiency, total pump power and pump station total head of each pump station are extracted; the pump station data and drainage well data are analyzed to determine the flow path length and flow path diameter between each pump station and different drainage wells connected to it; based on the pump station efficiency and total pump power, according to the flow path length and flow path diameter, the pump station regulation capacity of each pump station for each drainage well connected to it at a specified fluid velocity is determined; the sum of the self-drainage capacity and the pump station regulation capacity is taken as the drainage capacity of the corresponding drainage well, a drainage network directed graph is constructed based on the drainage well position, pump station position and drainage capacity, and the drainage network directed graph is used as the drainage network model.

[0052] The location of the drainage well may be the coordinate location of each drainage well in the corresponding urban area. The diameter of the drainage well may be the designed wellhead diameter of each drainage well. The vertical depth of the drainage well may be the length of the vertical part of the drainage well leading to the ground. The drainage path length may be the length of the connecting pipe path between the drainage well and the main drainage trunk. The self-drainage capacity evaluation model may be a mathematical model for quantifying the self-drainage capacity of the drainage well.

[0053] The specified fluid velocity may be the flow velocity of the sewage discharged from the drainage well in the drainage well. The self-drainage capacity may be the drainage capacity of the drainage well itself without the intervention of other auxiliary facilities. The pump station location may be the coordinate location of each pump station in the corresponding urban area. The pump station efficiency may be the ratio of the actual output mechanical energy to the input energy of the pump station during operation. The total pump power may be the total power required by the pump station during operation, which usually includes the input power of the pump and the power required by other auxiliary equipment.

[0054] The total head of a pumping station can be the total head height that the pumping station can overcome, reflecting the lifting capacity of the pumping station.

[0055] The flow path length may be the length of the connecting pipe between each drainage well and its corresponding pump station.

[0056] The flow path diameter may be the diameter of the connecting pipe between each drainage well and its corresponding pump station.

[0057] The regulating capacity of a pumping station may be the auxiliary capacity of the pumping station for the drainage capacity of each drainage well connected to it.

[0058] The drainage network directed graph may be directed graph data that characterizes the connectivity characteristics between each drainage well and pump station and the corresponding drainage capacity or regulation capacity.

[0059] Specifically, in the process of evaluating the drainage capacity of the drainage well, it is necessary to comprehensively consider the drainage capacity of the drainage well itself and the adjustment capacity of the external auxiliary equipment. Among them, the drainage capacity of the drainage well itself is mainly determined by the design and structural characteristics of the drainage well itself, mainly including the drainage well diameter, the vertical depth of the drainage well and the drainage path length. Through mathematical analysis, the mathematical influence relationship between the drainage well diameter, the vertical depth of the drainage well and the drainage path length and the drainage capacity of the drainage well itself is described, and a self-drainage capacity evaluation model is constructed to quantify the self-drainage capacity of each drainage well under a specified fluid velocity, so as to provide the influence data from the drainage well's own structure for the actual drainage capacity analysis of the drainage well.

[0060] The regulating capacity of external auxiliary equipment mainly depends on the drainage capacity of the pump station connected to the drainage well. The drainage capacity of the pump station is mainly affected by the efficiency of the pump station, the total pump power and the total head of the pump station. On this basis, since each pump station is usually connected to multiple drainage wells, there are differences in the connection paths between each drainage well and the pump station. Therefore, in the evaluation process of the drainage capacity of the drainage well, it is necessary to consider the interaction between the pump station and the drainage well. Based on the location of the drainage well, the location of the pump station and the corresponding connection relationship, the flow path length and flow path diameter between each pump station and the different drainage wells connected to it are extracted as mapping data for the subsequent analysis process of the interaction relationship between the pump station and the drainage well. Through further mathematical analysis, based on the pump station efficiency and the total pump power, according to the flow path length and the flow path diameter, the pump station regulation capacity of each pump station for each drainage well connected to it at a specified fluid velocity is quantified, providing the influence data from the pump station regulation effect for the actual drainage capacity analysis of the drainage well.

[0061] After determining its own drainage capacity and the regulating capacity of the pumping station, the sum of its own drainage capacity and the regulating capacity of the pumping station is used as the drainage capacity of the corresponding drainage well, and according to the location of the drainage well, the location of the pumping station and the drainage capacity, the location of the drainage well and the location of the pumping station are used as nodes of the directed graph respectively, the connectivity relationship between the drainage well and the corresponding pumping station is used as the path between the nodes of the directed graph, the drainage direction in the connectivity relationship is used as the path direction of the directed graph, and the drainage capacity is used as the data content of the drainage well node, so as to construct a drainage network directed graph, and use the drainage network directed graph as the drainage network model. When local changes occur in the urban drainage network, it is only necessary to add new nodes and paths to the existing drainage network directed graph in the above manner, or adjust the existing drainage network directed graph according to the changes in nodes and paths, so as to realize the dynamic update of the drainage network model and ensure the real-time nature of the subsequent waterlogging state analysis process.

[0062] Through this scheme, according to the drainage well diameter, vertical depth and drainage path length corresponding to the drainage well, a self-drainage capacity evaluation model is constructed to evaluate the self-drainage capacity of each drainage well. At the same time, based on the pump station efficiency and total pump power, according to the flow path length and flow path diameter, the pump station regulation capacity of each pump station for each drainage well connected to it is evaluated. On this basis, the drainage capacity of the drainage well is comprehensively evaluated, and a drainage network directed graph is constructed according to the drainage well location, pump station location and drainage capacity. The drainage network directed graph is used as the drainage network model to achieve highly abstract data processing of the urban drainage network. While scientifically evaluating the drainage capacity of the urban drainage network, the corresponding data structure is used to improve the dynamic expansion capability of the drainage network model to ensure the real-time nature of the subsequent waterlogging status analysis process.

[0063] In some embodiments, a self-drainage capacity evaluation model of each drainage well is constructed based on the drainage well diameter, the vertical depth of the drainage well, and the drainage path length, and the self-drainage capacity of each drainage well at a specified fluid velocity is determined by the following formula (1): (1) in, For the The drainage capacity of a drainage well, For the The diameter of the drainage well, For the The fluid velocity in the drainage well, is the friction coefficient of the preset path, For the The length of the drainage path of the drainage well, is the acceleration due to gravity, For the The vertical depth of the drainage well.

[0064] The preset path friction coefficient can be a value used to characterize the pressure loss caused by friction when the fluid flows in the drainage pipe. The preset path friction coefficient is determined by the drainage pipe material, and the preset path friction coefficient can be obtained by data fitting through the drainage pipe.

[0065] Specifically, through formula (1) Describes the fluid flow rate of the drainage well under the current fluid velocity. The fluid flow rate is positively correlated with the drainage capacity of the drainage well itself, and then through The head loss caused by friction loss and height difference in the drainage well is quantified, and finally the drainage capacity of each drainage well is scientifically quantified through formula (5) to accurately measure the drainage capacity of the drainage well under the influence of its own design structure.

[0066] Through this scheme, mathematical analysis methods are used, according to the diameter of the drainage well, the vertical depth of the drainage well and the length of the drainage path, and through mathematical language, a self-drainage capacity evaluation model is constructed to describe the influence of the above factors on the drainage capacity of the drainage well itself. The self-drainage capacity of each drainage well is scientifically quantified according to the self-drainage capacity evaluation model, so as to accurately measure the drainage capacity of the drainage well under the influence of its own design structure, and provide a solid data foundation for the subsequent analysis of the actual drainage capacity of the drainage well.

[0067] In some embodiments, based on the pump station efficiency and the total pump power, the pump station regulation capacity of each pump station for each drainage well connected thereto at a specified fluid velocity is determined according to the flow path length and the flow path diameter, specifically, the following formula (2): (2) in, For the The pump station is connected to the The pump station regulation capacity of each drainage well, is the pumping station efficiency, is the total pump power, is the preset average fluid density, is the total water head of the pumping station, is the friction coefficient of the preset path, For the Pumping station to The length of the flow path between the drainage wells, For the Pumping station to The velocity of the fluid in the flow path between the drainage wells, No. Pumping station to The diameter of the flow path between the drainage wells.

[0068] The preset average fluid density may be the average density of the fluid discharged from the drainage pipe, and the preset average fluid density may be obtained by fitting historical water body detection data.

[0069] Specifically, through formula (2) The head loss caused by friction loss in the flow path of the fluid is described and quantified. In this process, the flow path diameter is introduced to further improve the dynamic characteristics of the fluid in the flow path. That is, the larger the pipe diameter, the smaller the friction loss at the same flow rate. Describe the effective hydraulic head, and then through Describes the overall gravitational potential energy of the fluid in the flow path, while Quantify the output power of the pump station. The ratio of the output power of the pump station to the overall gravitational potential energy of the fluid reflects the ability of the current pump station to pump fluid in coordination with the current drainage well, thereby quantifying the regulation capacity of the pump station.

[0070] Through this scheme, mathematical analysis methods are used, based on the pump station efficiency and total pump power, according to the flow path length and flow path diameter, and mathematical language is used to clarify the influence of the above parameters on the regulating capacity of the pump station, so as to quantify the pump station regulating capacity of each drainage well connected to it at a specified fluid velocity, and then clarify the influence of the pump station on the drainage capacity of the drainage wells connected to it, further improving the accuracy and scientificity of the actual drainage capacity analysis process of the drainage wells.

[0071] In some embodiments, the relative terrain height of the location of each key facility is determined based on the terrain elevation data and the facility location data; based on the facility type data, the facility coverage area data is analyzed to determine the redundancy index and facility importance level of each key facility; the facility structure data is analyzed to determine the facility waterproof index of each key facility; based on the relative terrain height, redundancy index, facility importance level and facility structure data, the water accumulation sensitivity of each key facility is determined; based on the facility location data and water accumulation sensitivity, each key facility is labeled with its sensitivity; the labeled terrain elevation data and facility location data are subjected to unified spatial mapping processing to construct a regional basic model.

[0072] The terrain parameter set includes terrain elevation data.

[0073] The key facility parameter set includes facility location data, facility type data, facility structure data, and facility coverage area data.

[0074] Terrain elevation data can be digital information describing the ups and downs of the terrain in the current urban area.

[0075] The facility location data may be the location coordinate data of a key facility in the current urban area.

[0076] Relative terrain height: The relative height of the terrain corresponding to the location of the key facility within the current urban area.

[0077] The facility type data may be data used to characterize the type to which the critical facility belongs.

[0078] The facility structure data may be design structure parameters corresponding to key facilities.

[0079] The facility coverage area data may be the area information covered by the corresponding functions of the key facilities.

[0080] The redundancy index may be a numerical value used to characterize the degree of redundancy design of critical facilities.

[0081] The facility importance level may be information used to characterize the importance of key facilities in the current urban area.

[0082] The facility waterproof index may be a numerical value used to characterize the degree of waterproof design of key facilities.

[0083] Waterlogging sensitivity can be a quantitative value used to characterize whether key facilities are susceptible to waterlogging. The higher the waterlogging sensitivity, the more susceptible the current key facilities are to waterlogging.

[0084] Specifically, there are many types of key facilities located in urban areas, and they are widely distributed. When urban waterlogging occurs, different types of key facilities distributed in different locations are affected by waterlogging to different degrees. There are also differences in the scope of impact of abnormalities on key facilities after being affected by waterlogging. These differences are first affected by the relative terrain height corresponding to the location of the key facilities. The higher the relative terrain height of the location of the key facilities, the less likely they are to be affected. The relative terrain height of the key facilities can be determined based on the information corresponding to the facility location data in the terrain elevation data. Secondly, it is affected by the redundant design of key facilities and the importance level of facilities. If there are more redundant designs in key facilities, it means that even if part of the structure of the current key facilities is affected by waterlogging, it can rely on redundant designs to maintain normal status, so the key facilities are less likely to be affected by waterlogging. Redundant design can be reflected by the redundancy index evaluated during the design stage of key facilities; the importance level of facilities directly affects the severity of the consequences caused by the key facilities being affected by waterlogging. The higher the importance level of the key facilities, the more serious the consequences after being affected by waterlogging. The importance level of facilities is directly affected by the type of facilities and the area covered by the facilities. The type of facilities determines the absolute importance of the key facilities. The importance levels corresponding to different types of key facilities can be set according to the results of expert evaluation, and the coverage area of ​​the facilities determines the scope of the consequences caused after the key facilities are damaged by waterlogging. Whether the key facilities are susceptible to waterlogging is also affected by the facility waterproof index reflected in the facility structure data corresponding to the key facilities themselves. The higher the facility waterproof index, the more sufficient waterproof measures the key facilities have taken during the construction stage, and the key facilities are less likely to be affected by waterlogging.

[0085] Therefore, through mathematical analysis, the waterlogging sensitivity corresponding to key facilities is comprehensively quantified according to the relative terrain height, redundancy index, facility importance level, facility structure data and facility waterproof index, so as to reflect the sensitivity of key facilities to waterlogging under the influence of their location and their own status, and provide a scientific basis for the subsequent quantification of multi-dimensional risks caused by waterlogging. After determining the waterlogging sensitivity, each key facility is labeled with its sensitivity according to the facility location data and waterlogging sensitivity, and the terrain elevation data and facility location data after labeling are uniformly mapped in space to achieve effective integration of terrain data and key facility data, avoid the misalignment deviation between terrain data and key data, and thus construct an accurate regional basic model.

[0086] Through this plan, targeted analysis is conducted on the sensitivity of different types of key facilities to waterlogging at their locations based on relative terrain height, redundancy index, facility importance level, facility structural data and facility waterproof index, so as to scientifically reflect the sensitivity of different key facilities to waterlogging, provide a scientific basis for the subsequent quantification of multi-dimensional risks caused by waterlogging, and perform unified spatial mapping processing on the terrain elevation data and facility location data after annotation, build a regional basic model, avoid the misalignment deviation between terrain data and key data, and improve the accuracy and data consistency of the regional basic model.

[0087] In some embodiments, the water accumulation sensitivity of each key facility is determined based on the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index, specifically the following formula (3): (4) in, is the water accumulation sensitivity, For the facility importance level, is the preset magnification index, is the facility waterproof index, is the preset adjustment coefficient, is the redundancy index, is the preset redundancy influence coefficient, is the relative terrain height, is the preset decay index.

[0088] The preset amplification index can be a quantitative value used to adjust the impact of the importance level of a facility on the sensitivity of waterlogging. The preset amplification index can be obtained by fitting historical waterlogging data.

[0089] The preset adjustment coefficient may be a quantitative value used to adjust the effect of the waterproof index of the facility on the sensitivity of waterlogging. The preset adjustment coefficient may be obtained by fitting historical waterlogging data.

[0090] The preset redundancy impact coefficient may be a numerical value used to reflect the linear relationship between the redundancy index and the waterlogging sensitivity. The preset redundancy impact coefficient may be obtained by fitting historical waterlogging data.

[0091] The preset attenuation index can be a quantitative value used to adjust the attenuation characteristics of the influence of relative terrain height on waterlogging sensitivity, and the preset redundant influence coefficient can be obtained by fitting historical waterlogging data.

[0092] Specifically, through formula (4) Reflects the nonlinear positive correlation between the importance level of facilities and the sensitivity to waterlogging; Reflects the inverse proportional relationship between the facility waterproof index and water accumulation sensitivity, and through Adjust the degree of influence; Reflecting the complex impact of the redundancy index on waterlogging sensitivity, the use of a logarithmic function can prevent the sharp drop in waterlogging sensitivity caused by a high redundancy index, ensuring that the impact of the redundancy index on waterlogging sensitivity presents a diminishing return. Reflects the direct impact of relative terrain height on waterlogging sensitivity. The higher the relative terrain, the lower the waterlogging sensitivity. Control the impact of relative terrain height on waterlogging sensitivity; comprehensively consider the above impacts and scientifically quantify the waterlogging sensitivity of key facilities.

[0093] Through this plan, mathematical analysis methods are used to accurately quantify the water accumulation sensitivity of key facilities based on relative terrain height, redundancy index, facility importance level, facility structural data and facility waterproof index through clear mathematical relationships, thereby improving the scientificity and comprehensiveness of the water accumulation sensitivity analysis process, and thus improving the accuracy of the subsequent water accumulation risk analysis process based on water accumulation sensitivity.

[0094] In some embodiments, based on the flow rate information, the real-time drainage capacity of each drainage well is determined according to the drainage network model; based on the water collection information, the water collection area of ​​each drainage well is extracted; based on the regional basic model, the surface elevation of the well point of each drainage well is determined; based on the real-time rainfall, real-time drainage capacity and water collection area, the real-time runoff corresponding to each drainage well is determined to determine the total runoff; based on the real-time rainfall, total runoff, real-time drainage capacity and well point surface elevation, a water level change assessment model is constructed to assess the real-time water accumulation level; based on the water level change assessment model and rainfall change information, the real-time water accumulation level is updated according to the water flow dynamics equation; based on the regional basic model, the real-time water accumulation level is analyzed to determine the water accumulation risk information corresponding to different key facilities to determine a multi-dimensional risk information set.

[0095] The meteorological parameter set includes real-time rainfall, rainfall change information, water catchment information and flow rate information.

[0096] The real-time rainfall can be the rainfall corresponding to the current analysis time point.

[0097] The rainfall variation information may be information on the variation of rainfall over time.

[0098] The water collection information may be the information on the accumulation of surface water in the current urban area.

[0099] The flow rate information may be the flow rate information of the accumulated water in each drainage well.

[0100] The real-time drainage capacity may be the actual drainage capacity corresponding to each drainage at the current analysis time point.

[0101] The watershed area can be the area where surface water accumulates within the current analysis area.

[0102] The well point surface elevation may be elevation data corresponding to the wellhead position of the drainage well.

[0103] Real-time runoff can be the surface water flow information within the current analysis area.

[0104] The water level change assessment model can be a mathematical model used to characterize the temporal variation characteristics of the accumulated water level in the current analysis area.

[0105] The real-time ponding water level can be the height of the surface ponding water level in the current analysis area.

[0106] The waterlogging risk information may be the risk of critical facilities being affected by the current waterlogging status.

[0107] Specifically, after the drainage network model and the regional basic model are constructed in the manner of the aforementioned embodiments, the water flow velocity in each drainage well reflected in the flow velocity information is input into the drainage network model to quantify the real-time drainage capacity of each drainage well. The catchment area of ​​each drainage well in the area where the catchment information is located reflects the state of surface runoff at the wellhead of the drainage well. Changes in surface runoff directly affect the state of water accumulation in the area. The runoff at the wellhead of the drainage well is estimated based on the product of real-time rainfall and catchment area. Combined with the real-time drainage capacity of the drainage well, the real-time runoff at each wellhead is estimated, and by integrating the current The real-time runoff of each drainage well in the corresponding area of ​​the previous catchment area is used to determine the total runoff of the current catchment area. Through mathematical analysis, a water level change assessment model is constructed according to the real-time rainfall, total runoff, real-time drainage capacity and well surface elevation. The real-time waterlogging level is evaluated by solving the water level change assessment model. Based on the rainfall change information and the water flow dynamics equation, the changes in waterlogging level caused by rainfall changes in the regional basic model are tracked to achieve the update of the real-time waterlogging level. This is used as the dynamic data basis for determining the waterlogging risk information corresponding to different key facilities, so as to construct a multi-dimensional risk information set.

[0108] Through this solution, based on the meteorological parameter set, according to the drainage network model and the regional basic model, under dynamic precipitation changes, the drainage network model and the regional basic model are combined to jointly influence the development trend of waterlogging, build a water level change assessment model, and evaluate the real-time waterlogging level in the area. At the same time, combined with the water flow dynamics equation, the real-time waterlogging level is dynamically updated to track the real-time waterlogging level changes. This is used as the dynamic data basis for determining the corresponding waterlogging risk information of different key facilities, so as to construct a multi-dimensional risk information set, which significantly improves the accuracy and real-time performance of multi-dimensional risk judgment.

[0109] In some embodiments, a water level change assessment model is constructed based on real-time rainfall, total runoff, real-time drainage capacity and well point surface elevation, specifically the following formula (5): (5) in, The real-time water level. is the total runoff volume, For real-time rainfall, is the preset time step, For the The real-time drainage capacity of each drainage well, is the indicator function, For the The surface elevation of the well point of the drainage well; the hydrodynamic equation, specifically the following formula (6): (6) in, is the total runoff volume, is the runoff velocity vector, is the acceleration due to gravity, The real-time water level. is the terrain elevation gradient.

[0110] The preset time step may be a preset interval time step for evaluating the real-time water level, and the preset time step may be set according to specific analysis requirements.

[0111] The runoff velocity vector may be vector information used to characterize the velocity and direction of accumulated water. The runoff velocity vector may be derived based on the accumulated water velocity using the fluid continuity equation.

[0112] The terrain elevation gradient can be quantitative information reflecting the characteristics of terrain elevation change. The terrain elevation gradient can be obtained by gradient extraction of terrain elevation data based on terrain elevation data using a spatial difference algorithm.

[0113] The indicator function can be a function used to characterize and provide feedback on whether the function content is valid, such as Representative When , the function feedback data is 1, when , the function returns data as 0.

[0114] Specifically, through formula (5) Describes the contribution of rainfall within a preset time step; the drainage volume is determined by the drainage capacity of each drainage well and the water level relationship. The concept of water discharge is valid only when the water level is higher than the wellhead, which is expressed as , which is used to evaluate the amount of water discharged from the ponding. According to the principle of conservation of mass, the increase in the ponding water level minus the amount of water discharged from the drainage well is equal to the change in rainfall per unit time, which can be formally expressed as: , substituting the above rainfall contribution and water discharge into the above formal expression, the water level change assessment model corresponding to formula (5) is constructed. Further, based on the conservation of momentum and mass, the water flow dynamics equation corresponding to formula (6) is constructed, where It is used to describe the change of water flow in a unit volume over time and the effect of water flow velocity. Used to describe the gravity effect caused by real-time changes in water level in its corresponding terrain.

[0115] Through this plan, mathematical analysis methods are used to construct a water level change assessment model based on real-time rainfall, total runoff, real-time drainage capacity and well surface elevation through clear mathematical relationships to achieve the assessment of real-time waterlogging levels. In combination with the water flow dynamics equation, the real-time waterlogging level can be dynamically updated to provide scientific support for the determination of the real-time waterlogging level, improve the accuracy of the judgment of the real-time waterlogging level, and thus improve the accuracy of multi-dimensional risk judgment based on the real-time waterlogging level.

[0116] In some embodiments, according to the regional basic model, several key facilities located in the waterlogging area are determined; based on the real-time waterlogging water level, according to the waterlogging sensitivity corresponding to the several key facilities, the real-time waterlogging risk corresponding to each key facility is determined; according to the real-time waterlogging risk corresponding to each key facility and the facility coverage area data, the waterlogging risk information corresponding to the key facilities is constructed to determine a multi-dimensional risk information set.

[0117] Specifically, according to the real-time waterlogging level, the parameters of the corresponding key facilities in the regional basic model are analyzed, and several key facilities that will be affected by the real-time waterlogging level in the current waterlogging area are screened out, and further combined with the waterlogging sensitivity corresponding to the several key facilities, the waterlogging risk information of the above-mentioned several key facilities under the influence of their waterlogging sensitivity under the current real-time waterlogging level is determined. The risk establishment rule is: according to the real-time waterlogging level, the basic waterlogging risk of the above-mentioned several key facilities is determined. The basic waterlogging risk can be obtained by fitting the relationship coefficient between the waterlogging level and the basic waterlogging risk through historical waterlogging data and the product of the real-time waterlogging level, and the waterlogging risk information of the key facilities is obtained according to the product of the basic waterlogging risk and the waterlogging sensitivity of the corresponding key facilities. By integrating the waterlogging risk information of different key facilities and combining the facility coverage area data corresponding to the above-mentioned several key facilities, a multi-dimensional risk information set is obtained. The facility coverage area data can assist the corresponding positioning technology in the waterlogging warning process, such as cellular network positioning technology, to accurately delineate the impact ranges of different risks, and further assist in determining different target users within the impact ranges of different risks.

[0118] Through this solution, based on the real-time water level, the key facilities affected by the current waterlogging status are screened, and combined with the corresponding waterlogging sensitivity of the key facilities, the real-time waterlogging risk of the key facilities is evaluated, and the facility coverage area data corresponding to the key facilities are further integrated to obtain the waterlogging risk information corresponding to the key facilities. Based on this, a multi-dimensional risk information set is constructed to assist in the precise delineation of different risk impact ranges, and further assist in determining different target users within different risk impact ranges, thereby improving the pertinence and accuracy of the push of waterlogging warning information.

[0119] Figure 3 A schematic diagram of a waterlogging early warning system based on urban waterlogging simulation positioning is provided in an embodiment of the present application. Figure 3 As shown, a waterlogging warning system 300 based on urban waterlogging simulation positioning in this embodiment includes: a pipe network analysis module 301 , a regional analysis module 302 , a risk analysis module 303 and a warning module 304 .

[0120] The pipe network analysis module 301 is used to obtain the regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; the regional analysis module 302 is used to obtain the terrain parameter set and the key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model; the risk analysis module 303 is used to obtain the meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, simulate the development trend of waterlogging according to the regional basic model, and determine the multidimensional risk information set; the early warning module 304 is used to determine the target push user and the corresponding early warning push information based on the regional basic model and the multidimensional risk information set, and push the early warning push information to the target push user.

[0121] Optionally, the pipe network analysis module 301 is specifically used to: extract the drainage well position, drainage well diameter, drainage well vertical depth and drainage path length corresponding to each drainage well according to the drainage well data; construct a self-drainage capacity evaluation model for each drainage well according to the drainage well diameter, the drainage well vertical depth and the drainage path length, and thereby determine the self-drainage capacity of each drainage well at a specified fluid velocity; extract the pump station position, pump station efficiency, total pump power and total water head of each pump station according to the pump station data; analyze the pump station data and the drainage well data. According to the data, the flow path length and the flow path diameter between each pumping station and different drainage wells connected to it are determined; based on the pumping station efficiency and the total pump power, according to the flow path length and the flow path diameter, the pumping station regulation capacity for each drainage well connected to it under a specified fluid velocity is determined; the sum of the own drainage capacity and the pumping station regulation capacity is used as the drainage capacity of the corresponding drainage well, and a drainage network directed graph is constructed according to the drainage well location, the pumping station location and the drainage capacity, and the drainage network directed graph is used as the drainage network model.

[0122] Optionally, the pipe network analysis module 301 constructs a self-drainage capacity evaluation model for each drainage well according to the drainage well diameter, the vertical depth of the drainage well, and the drainage path length, and uses this to determine the self-drainage capacity of each drainage well at a specified fluid velocity, specifically the following formula: ; in, For the The self-drainage capacity of a drainage well, For the The diameter of the drainage well of the drainage well, For the The fluid velocity in the drainage well, is the friction coefficient of the preset path, For the The length of the drainage path of the drainage well, is the acceleration due to gravity, For the The vertical depth of the drainage well of a drainage well.

[0123] Optionally, the pipe network analysis module 301 determines the pump station regulation capacity of each pump station for each drainage well connected thereto at a specified fluid velocity based on the pump station efficiency and the total pump power, according to the flow path length and the flow path diameter, specifically the following formula: ; in, For the The pump station is connected to the The pump station regulation capacity of the drainage wells, is the pumping station efficiency, is the total pump power, is the total water head of the pumping station, is the friction coefficient of the preset path, For the Pumping station to The length of the flow path between the drainage wells, For the Pumping station to The velocity of the fluid in the flow path between the drainage wells, No. Pumping station to The flow path diameter between the drainage wells.

[0124] Optionally, the regional analysis module 302 is specifically used to: determine the relative terrain height of the location of each key facility based on the terrain elevation data and the facility location data; analyze the facility coverage area data based on the facility type data to determine the redundancy index and facility importance level of each key facility; analyze the facility structure data to determine the facility waterproof index of each key facility; determine the water accumulation sensitivity of each key facility based on the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index; label the sensitivity of each key facility based on the facility location data and the water accumulation sensitivity; and perform unified spatial mapping processing on the terrain elevation data and the facility location data after labeling to construct the regional basic model.

[0125] Optionally, when the regional analysis module 302 determines the water accumulation sensitivity of each key facility according to the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index, it is specifically the following formula: ;in, is the water accumulation sensitivity, is the importance level of the facility, is the preset magnification index, is the waterproof index of the facility, is the preset adjustment coefficient, is the redundancy index, is the preset redundancy influence coefficient, is the relative terrain height, is the preset decay index.

[0126] Optionally, the risk analysis module 303 is specifically used to: determine the real-time drainage capacity of each drainage well based on the flow velocity information and the drainage network model; extract the drainage area of ​​each drainage well based on the water collection information; determine the surface elevation of the well point of each drainage well based on the regional basic model; determine the real-time runoff corresponding to each drainage well based on the real-time rainfall, the real-time drainage capacity and the drainage area, so as to determine the total runoff; construct a water level change assessment model based on the real-time rainfall, the total runoff, the real-time drainage capacity and the well point surface elevation to assess the real-time waterlogging level; based on the water level change assessment model and the rainfall change information, update the real-time waterlogging level according to the water flow dynamics equation; analyze the real-time waterlogging level based on the regional basic model, and determine the waterlogging risk information corresponding to different key facilities, so as to determine the multi-dimensional risk information set.

[0127] Optionally, when the risk analysis module 303 constructs a water level change assessment model according to the real-time rainfall, the total runoff, the real-time drainage capacity and the well point surface elevation, the specific formula is as follows: ; in, is the real-time accumulated water level, is the total runoff volume, is the real-time rainfall, is the preset time step, For the The real-time drainage capacity of the drainage wells, is the indicator function, For the The surface elevation of the well point of a drainage well; the hydrodynamic equation is specifically the following formula: ;in, is the total runoff volume, is the runoff velocity vector, is the acceleration due to gravity, is the real-time accumulated water level, is the terrain elevation gradient.

[0128] Optionally, when the risk analysis module 303 analyzes the real-time waterlogging level based on the regional basic model and determines the waterlogging risk information corresponding to different key facilities to determine the multidimensional risk information set, it is specifically used to: determine a number of key facilities within the waterlogging area according to the regional basic model; determine the real-time waterlogging risk corresponding to each key facility based on the real-time waterlogging level and the waterlogging sensitivity corresponding to the several key facilities; construct the waterlogging risk information corresponding to the key facilities according to the real-time waterlogging risk corresponding to each key facility and the facility coverage area data to determine the multidimensional risk information set.

[0129] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A waterlogging early warning method based on urban waterlogging simulation positioning, characterized in that: include: Acquire a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; Acquire a terrain parameter set and a key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model; Acquire a meteorological parameter set, and based on the meteorological parameter set and the drainage network model, simulate the development trend of waterlogging according to the regional basic model, and thereby determine a multidimensional risk information set; Based on the regional basic model and according to the multi-dimensional risk information set, a target push user and corresponding warning push information are determined, and the warning push information is pushed to the target push user.

2. The method according to claim 1, characterized in that The pipe network parameter set includes drainage well data and pump station data. The analyzing the regional pipe network parameter set to construct a drainage pipe network model includes: Extracting the drainage well position, drainage well diameter, drainage well vertical depth and drainage path length corresponding to each drainage well according to the drainage well data; According to the diameter of the drainage well, the vertical depth of the drainage well and the length of the drainage path, a self-drainage capacity evaluation model of each drainage well is constructed, and the self-drainage capacity of each drainage well under a specified fluid velocity is determined thereby; Extracting the pumping station location, pumping station efficiency, total pump power and total water head of each pumping station based on the pumping station data; Analyzing the pump station data and the drainage well data to determine the flow path length and flow path diameter between each pump station and different drainage wells connected thereto; determining, based on the pump station efficiency and the total pump power, a pump station regulation capacity of each pump station for each drainage well connected thereto at a specified fluid velocity according to the flow path length and the flow path diameter; The sum of the self-drainage capacity and the regulating capacity of the pump station is taken as the drainage capacity of the corresponding drainage well. According to the location of the drainage well, the location of the pump station and the drainage capacity, a drainage network directed graph is constructed, and the drainage network directed graph is used as the drainage network model.

3. The method according to claim 2, characterized in that According to the drainage well diameter, the vertical depth of the drainage well and the drainage path length, a self-drainage capacity evaluation model of each drainage well is constructed, and the self-drainage capacity of each drainage well at a specified fluid velocity is determined by the following formula: ； in, For the The self-drainage capacity of a drainage well, For the The diameter of the drainage well of the drainage well, For the The fluid velocity in the drainage well, is the friction coefficient of the preset path, For the The length of the drainage path of the drainage well, is the acceleration due to gravity, For the The vertical depth of the drainage well of a drainage well.

4. The method according to claim 2, characterized in that: Based on the pump station efficiency and the total pump power, the pump station regulation capacity of each pump station for each drainage well connected thereto at a specified fluid velocity is determined according to the flow path length and the flow path diameter, specifically as follows: ； in, For the The pump station is connected to the The pumping station regulation capacity of the drainage wells, is the pumping station efficiency, is the total pump power, is the total water head of the pumping station, is the friction coefficient of the preset path, For the Pumping station to The length of the flow path between the drainage wells, For the Pumping station to The velocity of the fluid in the flow path between the drainage wells, No. Pumping station to The flow path diameter between the drainage wells.

5. The method according to claim 2, characterized in that: The terrain parameter set includes terrain elevation data, the key facility parameter set includes facility location data, facility type data, facility structure data and facility coverage area data, and the step of analyzing the terrain parameter set and the key facility parameter set to construct a regional basic model includes: Determining the relative terrain height of each key facility location based on the terrain elevation data and the facility location data; Based on the facility type data, analyzing the facility coverage area data, determining the redundancy index and facility importance level of each key facility; Analyze the facility structure data to determine the facility waterproof index of each key facility; Determining the water accumulation sensitivity of each key facility according to the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index; According to the facility location data and the water accumulation sensitivity, each key facility is labeled with a sensitivity; The terrain elevation data and the facility location data after annotation are uniformly mapped to construct the regional basic model.

6. The method according to claim 5, characterized in that The water accumulation sensitivity of each key facility is determined according to the relative terrain height, the redundancy index, the facility importance level, the facility structure data and the facility waterproof index, specifically the following formula: ； in, is the water accumulation sensitivity, is the importance level of the facility, is the preset magnification index, is the waterproof index of the facility, is the preset adjustment coefficient, is the redundancy index, is the preset redundancy influence coefficient, is the relative terrain height, is the preset decay index.

7. The method according to claim 5, characterized in that The meteorological parameter set includes real-time rainfall, rainfall change information, water collection information and flow rate information. Based on the meteorological parameter set and the drainage network model, according to the regional basic model, the development trend of waterlogging is simulated, and a multi-dimensional risk information set is determined, including: Based on the flow rate information and the drainage network model, determining the real-time drainage capacity of each drainage well; Extracting the catchment area of ​​each drainage well according to the catchment information; Determine the surface elevation of each drainage well point according to the regional basic model; Determine the real-time runoff corresponding to each drainage well according to the real-time rainfall, the real-time drainage capacity and the catchment area, thereby determining the total runoff amount; Constructing a water level change assessment model according to the real-time rainfall, the total runoff, the real-time drainage capacity and the surface elevation of the well point to assess the real-time accumulated water level; Based on the water level change assessment model and the rainfall change information, the real-time accumulated water level is updated according to the water flow dynamics equation; Based on the regional basic model, the real-time flooding water level is analyzed to determine the flooding risk information corresponding to different key facilities, thereby determining the multi-dimensional risk information set.

8. The method according to claim 7, characterized in that The water level change assessment model is constructed according to the real-time rainfall, the total runoff, the real-time drainage capacity and the surface elevation of the well point, which is specifically the following formula: ； in, is the real-time accumulated water level, is the total runoff volume, is the real-time rainfall, is the preset time step, For the The real-time drainage capacity of the drainage wells, is the indicator function, For the The surface elevation of the well point of each drainage well; The hydrodynamic equation is specifically the following formula: ； in, is the total runoff volume, is the runoff velocity vector, is the acceleration due to gravity, is the real-time accumulated water level, is the terrain elevation gradient.

9. The method according to claim 7, characterized in that: The method of analyzing the real-time flooding water level based on the regional basic model and determining the flooding risk information corresponding to different key facilities, thereby determining the multi-dimensional risk information set, includes: According to the regional basic model, several key facilities located in the waterlogged area are determined; Based on the real-time flooding water level, and according to the flooding sensitivity corresponding to the plurality of key facilities, determining the real-time flooding risk corresponding to each key facility; According to the real-time waterlogging risk corresponding to each key facility and the facility coverage area data, the waterlogging risk information corresponding to the key facilities is constructed to determine the multi-dimensional risk information set.

10. A waterlogging early warning system based on urban waterlogging simulation and positioning, characterized in that: include: A pipe network analysis module, used to obtain a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; A regional analysis module, used to obtain a terrain parameter set and a key facility parameter set, analyze the terrain parameter set and the key facility parameter set, and construct a regional basic model; A risk analysis module, used for obtaining a meteorological parameter set, simulating the development trend of waterlogging based on the meteorological parameter set and the drainage network model and the regional basic model, and determining a multi-dimensional risk information set based on the same; The early warning module is used to determine the target push user and the corresponding early warning push information based on the regional basic model and the multi-dimensional risk information set, and push the early warning push information to the target push user.

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