A waterlogging warning method and system based on urban waterlogging simulation and positioning

Abstract

This application relates to the field of disaster warning technologies, and particularly to a waterlogging warning method and system based on urban waterlogging simulation and positioning. The method includes: obtaining a regional pipe network parameter set, analyzing the regional pipe network parameter set, and constructing a drainage pipe network model; obtaining 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; obtaining a meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, and according to the regional basic model, simulating the development trend of waterlogging, and thereby determining a multi-dimensional risk information set; based on the regional basic model, according to the multi-dimensional risk information set, determining target push users and corresponding warning push information, and pushing the warning push information to the target push users. This application can accurately reflect the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and effectively improve the accuracy, real-time performance, and pertinence of the waterlogging warning process.

Description

Technical Field

[0001] This application relates to the technical field of disaster warning, and particularly to a waterlogging warning method and system 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 precipitation weather, the urban drainage system is facing huge pressure, resulting in an increase in the frequency of urban waterlogging, bringing huge challenges to citizens' lives, infrastructure, and urban management.

[0003] Traditional urban waterlogging warning technologies usually rely on single-dimensional meteorological data, such as rainfall, rainfall intensity, rainfall duration, etc. to predict waterlogging risks, and it is difficult to reflect the comprehensive impact of waterlogging under multi-dimensional complex factors in the city, resulting in problems such as too large data granularity, low warning real-time performance, and weak target pertinence in the waterlogging warning process. Summary of the Invention

[0004] This application provides a waterlogging warning method and system based on urban waterlogging simulation and positioning to solve the above technical problems.

[0005] In the first aspect, this application provides a waterlogging warning method based on urban waterlogging simulation and positioning, and the method includes:

[0006] Obtain a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; 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; obtain a meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, according to the regional basic model, simulate the development trend of waterlogging, and thereby determine a multi-dimensional risk information set; based on the regional basic model, according to the multi-dimensional risk information set, determine the target push users and the corresponding warning push information, and push the warning push information to the target push users.

[0007] Through this solution, analyze the regional pipe network parameter set, terrain parameter set, and key facility parameter set, and construct a drainage pipe network model and a regional basic model, providing scientific data support for evaluating the risks brought by the dynamic development process of waterlogging. Based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, simulate the dynamic waterlogging development trend formed after the dynamic precipitation is affected by the drainage pipe network model on the regional basic model, thereby analyzing the multi-dimensional risks brought by the waterlogging development process, obtaining a multi-dimensional risk information set, accurately reflecting the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and on this basis, combining with the regional basic model, determine the target push users and the corresponding warning push information, and push the warning push information to the target push users, significantly improving the target pertinence of waterlogging warning information.

[0008] Optionally, the set of pipe network parameters includes drainage well data and pumping station data. Analyzing the set of regional pipe network parameters and constructing a drainage pipe network model includes:

[0009] According to the drainage well data, extract the drainage well location, drainage well diameter, drainage well vertical depth, and drainage path length corresponding to each drainage well; according to the drainage well diameter, the drainage well vertical depth, and the drainage path length, construct an evaluation model for the self-drainage capacity of each drainage well, and thereby determine the self-drainage capacity of each drainage well at a specified fluid velocity; according to the pumping station data, extract the pumping station location, pumping station efficiency, total pump power, and total head of the pumping station; analyze the pumping station data and the drainage well data to determine the flow path length and flow path diameter between each pumping station and different drainage wells connected to it; based on the pumping station efficiency and the total pump power, according to the flow path length and the flow path diameter, determine the pumping station regulation capacity of each pumping station for each drainage well connected to it at a specified fluid velocity; take the sum of the self-drainage capacity and the pumping station regulation capacity as the drainage capacity of the corresponding drainage well, and construct a directed graph of the drainage pipe network according to the drainage well location, the pumping station location, and the drainage capacity, and use the directed graph of the drainage pipe network as the drainage pipe network model.

[0010] Through this solution, according to the drainage well diameter, drainage well vertical depth, and drainage path length corresponding to the drainage well, construct an evaluation model for the self-drainage capacity to evaluate the self-drainage capacity of each drainage well. At the same time, based on the pumping station efficiency and total pump power, according to the flow path length and flow path diameter, evaluate the pumping station regulation capacity of each pumping station for each drainage well connected to it. On this basis, comprehensively evaluate the drainage capacity of the drainage well, and construct a directed graph of the drainage pipe network according to the drainage well location, pumping station location, and drainage capacity, and use the directed graph of the drainage pipe network as the drainage pipe network model to achieve a high degree of data abstraction for the urban drainage pipe network. While scientifically evaluating the drainage capacity of the urban drainage pipe network, through the corresponding data structure, improve the dynamic expansion ability of the drainage pipe network model and ensure the real-time nature of the subsequent analysis process of the water accumulation state.

[0011] Optionally, the construction of an evaluation model for the self-drainage capacity of each drainage well according to the drainage well diameter, the drainage well vertical depth, and the drainage path length, and thereby determining the self-drainage capacity of each drainage well at a specified fluid velocity is specifically the following formula:

[0012] ;

[0013] Wherein, is the self-drainage capacity of the th drainage well, the diameter of the drainage well for the th fluid velocity in the th drainage well, is the preset path friction coefficient, the drainage path length of the th drainage well, is the acceleration due to gravity, the vertical depth of the

[0014] Through this solution, by means of mathematical analysis, according to the diameter of the drainage well, the vertical depth of the drainage well, and the drainage path length, a self-drainage capacity evaluation model for describing the influence of the above factors on the self-drainage capacity of the drainage well is constructed in mathematical language, and the self-drainage capacity of each drainage well is scientifically quantified according to the self-drainage capacity evaluation model to accurately measure the drainage capacity of the drainage well under the influence of its own design structure, providing a solid data basis for the subsequent analysis of the actual drainage capacity of the drainage well.

[0015] Optionally, based on the pump station efficiency and the total pump power, according to the flow path length and the flow path diameter, determine the pump station adjustment ability of each pump station for each drainage well connected to it at a specified fluid velocity, specifically as the following formula:

[0016] ;

[0017] where is the pump station adjustment ability of the th pump station for the th drainage well connected to it, is the pump station efficiency, is the total pump power, is the total head of the pump station, is the preset path friction coefficient, is the th pump station to the th drainage well is the th pump station to the fluid velocity in the flow path between the th pump station and the th drainage well, the flow path diameter between the

[0018] Through this solution, by means of mathematical analysis, based on the pump station efficiency and the total pump power, according to the length and diameter of the flow path, the influence of the above parameters on the regulation ability of the pump station is clarified through mathematical language, so as to quantitatively obtain the regulation ability of each pump station to each drainage well connected to it at a specified fluid velocity, and further clarify the influence of the pump station on the drainage ability of the drainage well connected to it, further improving the accuracy and scientificity of the analysis process of the actual drainage ability of the drainage well.

[0019] Optionally, the topographic parameter set includes topographic elevation data, and the key facility parameter set includes facility location data, facility type data, facility structure data, and facility coverage area data. Analyzing the topographic parameter set and the key facility parameter set to construct a regional basic model includes:

[0020] According to the topographic elevation data and the facility location data, determine the relative topographic height of the location of each key facility; based on the facility type data, analyze the facility coverage area 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; according to the relative topographic height, the redundancy index, the facility importance level, the facility structure data, and the facility waterproof index, determine the waterlogging sensitivity of each key facility; according to the facility location data and the waterlogging sensitivity, perform sensitivity marking on each key facility; perform unified spatial mapping processing on the marked topographic elevation data and facility location data to construct the regional basic model.

[0021] Through this solution, according to the relative topographic height, redundancy index, facility importance level, facility structure data, and facility waterproof index, conduct targeted analysis on the waterlogging sensitivity of different types of key facilities at their locations, so as to scientifically reflect the sensitivity of different key facilities to the impact of waterlogging, provide a scientific basis for quantifying the multi-dimensional risks caused by waterlogging in the follow-up, and perform unified spatial mapping processing on the marked topographic elevation data and facility location data to construct a regional basic model, avoiding the situation of misalignment deviation between topographic data and key data, and improving the accuracy and data consistency of the regional basic model.

[0022] Optionally, determining the waterlogging sensitivity of each key facility according to the relative topographic height, the redundancy index, the facility importance level, the facility structure data, and the facility waterproof index is specifically the following formula:

[0023] ;

[0024] Wherein, is the waterlogging sensitivity, is the facility importance level, is a preset amplification index, is the waterproof index of the said facility, is a preset adjustment coefficient, is the said redundancy index, is a preset redundancy influence coefficient, is the said relative terrain height, is a preset attenuation index.

[0025] Through this solution, by means of mathematical analysis, based on the relative terrain height, redundancy index, facility importance level, facility structure data and facility waterproof index, through clear mathematical relationships, the waterlogging sensitivity of key facilities is accurately quantified, improving the scientificity and comprehensiveness of the waterlogging sensitivity analysis process, and thus improving the accuracy of the subsequent waterlogging risk analysis process based on waterlogging sensitivity.

[0026] Optionally, the meteorological parameter set includes real-time rainfall, rainfall change information, catchment information and flow velocity information. Based on the meteorological parameter set and the drainage pipe 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:

[0027] Based on the flow velocity information, according to the drainage pipe network model, determine the real-time drainage capacity of each drainage well; according to the catchment information, extract the catchment area of each drainage well; according to the regional basic model, determine the ground elevation of the well point of each drainage well; according to the real-time rainfall, the real-time drainage capacity and the catchment area, determine the real-time runoff volume corresponding to each drainage well, and thus determine the total runoff volume; according to the real-time rainfall, the total runoff volume, the real-time drainage capacity and the ground elevation of the well point, construct a water level change evaluation model to evaluate the real-time waterlogging level; based on the water level change evaluation model and the rainfall change information, according to the hydrodynamic equation, update the real-time waterlogging level; based on the regional basic model, analyze the real-time waterlogging level, determine the waterlogging risk information corresponding to different key facilities, and thus determine the multi-dimensional risk information set.

[0028] Through this solution, based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, under dynamic precipitation changes, under the combined influence of the drainage pipe network model and the regional basic model, the development trend of waterlogging is simulated, a water level change evaluation model is constructed to evaluate the real-time waterlogging level in the region, and at the same time, combined with the hydrodynamic equation, the real-time waterlogging level is dynamically updated to realize the tracking of the real-time waterlogging level change, which is used as the dynamic data basis for determining the waterlogging risk information corresponding to different key facilities to construct a multi-dimensional risk information set, significantly improving the accuracy and real-time performance of multi-dimensional risk judgment.

[0029] Optionally, the water level change evaluation model is constructed based on the real-time rainfall, the total runoff volume, the real-time drainage capacity, and the well point ground elevation, specifically as the following formula:

[0030] ;

[0031] where, is the real-time ponding water level, is the total runoff volume, is the real-time rainfall, is the preset time step, is the th real-time drainage capacity of the drainage well, is the indicator function, is the well point ground elevation of the

[0032] ;

[0033] where, is the total runoff volume, is the runoff velocity vector, is the acceleration of gravity, is the real-time ponding water level, is the terrain elevation gradient.

[0034] Through this solution, by using mathematical analysis means, based on the real-time rainfall, the total runoff volume, the real-time drainage capacity, and the well point ground elevation, through clear mathematical relationships, a water level change evaluation model is constructed to realize the evaluation of the real-time ponding water level, and combined with the water flow dynamics equation, the dynamic update of the real-time ponding water level is realized, providing scientific support for the determination of the real-time ponding water level, improving the accuracy of the judgment of the real-time ponding water level, and further improving the accuracy of the multi-dimensional risk judgment based on the real-time ponding water level.

[0035] Optionally, based on the regional basic model, the real-time ponding water level is analyzed to determine the ponding risk information corresponding to different key facilities, so as to determine the multi-dimensional risk information set, including:

[0036] Based on the regional basic model, several key facilities located in the ponding area are determined; based on the real-time ponding water level, according to the ponding sensitivity corresponding to the several key facilities, the real-time ponding risk corresponding to each key facility is determined; according to the real-time ponding risk corresponding to each key facility and the facility coverage area data, the ponding risk information corresponding to the key facility is constructed, so as to determine the multi-dimensional risk information set.

[0037] Through this solution, based on the real-time waterlogging level, key facilities affected under the current waterlogging state are screened, and combined with the waterlogging sensitivity corresponding to the key facilities, the real-time waterlogging risk of the key facilities is evaluated. Further, the data of the facility coverage areas corresponding to the key facilities is integrated to obtain the waterlogging risk information corresponding to the key facilities, and a multi-dimensional risk information set is constructed based on this, to assist in the accurate delimitation of different risk impact ranges, and further assist in determining different target users within different risk impact ranges, improving the pertinence and accuracy of the waterlogging warning information push.

[0038] In a second aspect, the present application provides a waterlogging warning system based on urban waterlogging simulation and positioning. The system includes:

[0039] A pipe network analysis module, configured to obtain a set of regional pipe network parameters, analyze the set of regional pipe network parameters, and construct a drainage pipe network model; a regional analysis module, configured to obtain a set of terrain parameters and a set of key facility parameters, analyze the set of terrain parameters and the set of key facility parameters, and construct a regional basic model; a risk analysis module, configured to obtain a set of meteorological parameters, based on the set of meteorological parameters and the drainage pipe network model, according to the regional basic model, simulate the development trend of waterlogging, and thereby determine a multi-dimensional risk information set; an early warning module, configured to based on the regional basic model, according to the multi-dimensional risk information set, determine target push users and corresponding warning push information, and push the warning push information to the target push users. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0042] Figure 2 It is a flowchart of a waterlogging warning method based on urban waterlogging simulation and positioning provided by an embodiment of the present application;

[0043] Figure 3 It is a schematic structural diagram of a waterlogging warning system based on urban waterlogging simulation and positioning provided by an embodiment of the present application;

[0044] Figure 4 It is an operation interface diagram of a waterlogging warning system based on urban waterlogging simulation and positioning provided by an embodiment of the present application. Detailed Embodiments

[0045] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts shall fall within the protection scope of this application.

[0046] In addition, the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, unless otherwise specified.

[0047] The embodiments of this application will be further described in detail below with reference to the accompanying drawings of the specification.

[0048] 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 complex factors in the city, resulting in problems such as too large data granularity, low warning real-time performance, and weak target pertinence in the waterlogging warning process.

[0049] Based on this, this application provides a waterlogging warning method and system based on urban waterlogging simulation and positioning. By analyzing the regional pipe network parameter set, terrain parameter set, and key facility parameter set, a drainage pipe network model and a regional basic model are constructed to provide scientific data support for evaluating the risks brought by the dynamic development process of waterlogging. Based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, the dynamic development trend of waterlogging formed after the dynamic precipitation is affected by the drainage pipe network model on the regional basic model is simulated, so as to analyze the multi-dimensional risks brought by the waterlogging development process, obtain a multi-dimensional risk information set, accurately reflect the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and on this basis, in combination with the regional basic model, determine the target push users and the corresponding warning push information, and push the warning push information to the target push users, significantly improving the target pertinence of the waterlogging warning information.

[0050] Figure 1 This is a schematic diagram of an application scenario provided by this application. In the process of urban waterlogging warning, applying the method provided by this application can accurately reflect the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and effectively improve the accuracy, real-time performance, and pertinence of the waterlogging warning process.

[0051] 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 critical 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 critical facility parameter set provided by the critical facility management department, constructs a drainage pipe network model and a regional basic model, provides scientific data support for evaluating the risks brought by the dynamic development process of waterlogging, and based on the meteorological parameter set provided by the local meteorological department, according to the drainage pipe network model and the regional basic model, simulates the dynamic waterlogging development trend formed after the dynamic precipitation is affected by the drainage pipe network model on the regional basic model, analyzes the multi-dimensional risks brought by the waterlogging development process, obtains a multi-dimensional risk information set, accurately reflects the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and on this basis, combines with the regional basic model to determine the target push users and the corresponding warning push information, and pushes the warning push information to the target push users, significantly improving the target pertinence of the waterlogging warning information.

[0052] Specific implementation manners can refer to the following embodiments.

[0053] Figure 2 The flowchart of a waterlogging warning method based on urban waterlogging simulation and positioning provided by an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. As Figure 2 shown, the method includes:

[0054] S201. Obtain a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model.

[0055] The regional pipe network parameter set can be a set of drainage pipe network parameters in the waterlogging area of the city to be monitored, and can include geometric data, pipe diameter data, etc. The regional pipe network parameter set can be provided by the municipal management department.

[0056] The drainage pipe network model can be a mathematical model used to characterize the characteristics of the drainage pipe network in the region.

[0057] Specifically, in the process of urban waterlogging early warning, quickly and accurately analyzing the waterlogging status of each urban area is a necessary prerequisite for improving the timeliness and accuracy of waterlogging early 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 the urbanization process and the implementation of pipe network maintenance work, local changes often occur in the urban drainage pipe network system. 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 to obtain a drainage pipe network model, which can provide real-time and refined data support for subsequent waterlogging status analysis. Moreover, when local changes occur in the drainage pipe network system, it can be dynamically updated to ensure that accurate drainage pipe network information can be quickly obtained from it in the subsequent waterlogging status analysis process.

[0058] 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.

[0059] The terrain parameter set can be a set of terrain parameters within the urban area that is the object of waterlogging monitoring, and can include the terrain elevation information of each urban area. The terrain parameter set can be provided by the local remote sensing system.

[0060] The key facility parameter set can be a set of public facility parameters within the urban area that have a key impact on the production and life of residents. The key facility parameter set can be provided by the key facility management department.

[0061] The regional basic model can be a mathematical model used to characterize the terrain and key facility characteristics within the urban area.

[0062] Specifically, the development trend of urban waterlogging is directly affected by the terrain features of different regions within the city in addition to the influence of the drainage pipe network. The change in the terrain slope within the city directly determines the flow and convergence direction of precipitation on the urban surface, thereby affecting the distribution state of waterlogging in each urban area. By comprehensively analyzing the urban terrain features and drainage pipe network characteristics, it is possible to track the changes in the development trend of waterlogging in each urban area. However, the magnitude of the impact of waterlogging on its surrounding area cannot be evaluated solely from the perspectives of water volume and waterlogging duration. The production and life of urban residents rely on key public facilities distributed throughout the city, such as power facilities and water supply facilities. If these facilities are damaged by waterlogging during an urban flood, then even if the water volume and waterlogging duration do not reach the current urban flood classification standard, the resulting impact cannot be ignored. Moreover, 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 scope during the waterlogging warning process. The division of target objects and warning scope is no longer solely determined by the waterlogging diffusion state. Instead, as the waterlogging situation develops and more key facilities are at risk of being damaged by waterlogging, the affected area of waterlogging caused by the damage of key facilities will spread outward from the location of the key facilities, centered on their specific responsible areas. At the same time, the target objects affected will change during this process. For example, if a power facility is damaged by waterlogging, the corresponding warning scope should be expanded to the power supply area responsible for by this power facility. In addition to the residents in the waterlogging diffusion area, the residents within the power supply area corresponding to this power facility should also be included in the warning target objects. By introducing key facilities into the waterlogging situation analysis process, the judgment of the impact of waterlogging becomes more comprehensive and user-friendly, and it has important guiding significance for accurately defining the warning target and scope in the subsequent waterlogging warning process. By using mathematical analysis methods to analyze the terrain parameter set and key facility parameter set and constructing a regional basic model, scientific data support can be provided for the above analysis process.

[0063] S203. Obtain a meteorological parameter set. Based on the meteorological parameter set and the drainage pipe network model, and according to the regional basic model, simulate the development trend of waterlogging and thereby determine a multi-dimensional risk information set.

[0064] The meteorological parameter set can be a set of local meteorological parameters within the urban area, and the meteorological parameter set can be provided by the local meteorological system. The development trend of waterlogging can be the diffusion trend of waterlogging within its urban area.

[0065] The multi-dimensional risk information set can be a set of multi-dimensional risk information triggered by waterlogging within its urban area.

[0066] Specifically, the development trend of urban waterlogging is directly affected by meteorological changes. After constructing the drainage pipe network model and the regional basic model, by introducing the meteorological change information corresponding to the meteorological parameter set and using further mathematical analysis methods, the dynamic waterlogging development trend formed after the dynamic precipitation brought by the meteorological change information is affected by the drainage pipe network model on the regional basic model can be accurately simulated. As the dynamic waterlogging development trend changes, the impact risks on different types of key facilities in the urban area where the waterlogging is located also change accordingly. Moreover, the specific risks generated after different types of key facilities are affected by waterlogging are in different dimensions. Therefore, the risk changes brought by the dynamic waterlogging development trend show a multi-dimensional development trend. According to the simulated waterlogging development trend, combined with the parameters of various types of key facilities in the regional basic model, through mathematical analysis methods, the multi-dimensional risks brought during the waterlogging development process are quantified, and then a multi-dimensional risk information set is obtained to support the subsequent targeted technical warning process.

[0067] S204. Based on the regional basic model, according to the multi-dimensional risk information set, determine the target push users and the corresponding warning push information, and push the warning push information to the target push users.

[0068] The target push users can be the users who need to be reminded corresponding to the multi-dimensional risks caused by waterlogging in the current urban area. The warning push information can be the targeted push information for warning the target users regarding the different risks caused by waterlogging.

[0069] Specifically, after determining the multi-dimensional risk information set, based on the different risks reflected by the multi-dimensional risk information set, according to the regional basic model, combined with the corresponding key facility parameters therein, delimit the scope affected by different risks. At the same time, according to the types to which different risks belong, extract the corresponding warning information from the preset information template database, and according to the scope affected by different risks, through the cellular network positioning technology, determine the target users within the scope and push the corresponding warning information to the data terminals owned by the target users, such as mobile phones, so that the target users can clearly understand the risks brought by the current waterlogging they face.

[0070] Through this solution, analyze the regional pipe network parameter set, terrain parameter set, and key facility parameter set, construct a drainage pipe network model and a regional basic model, provide scientific data support for evaluating the risks brought by the dynamic development process of waterlogging, and based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, simulate the dynamic waterlogging development trend formed after the dynamic precipitation is affected by the drainage pipe network model on the regional basic model, so as to analyze the multi-dimensional risks brought by the waterlogging development process, obtain a multi-dimensional risk information set, accurately reflect the real-time comprehensive impact of waterlogging under multi-dimensional complex factors in the city, and on this basis, combine with the regional basic model, determine the target push users and the corresponding warning push information, and push the warning push information to the target push users, significantly improving the target pertinence of the waterlogging warning information.

[0071] In some embodiments, according to the drainage well data, 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 diameter, drainage well vertical depth, and drainage path length, construct an evaluation model for the self-drainage capacity of each drainage well, and thereby determine the self-drainage capacity of each drainage well at a specified fluid velocity; according to the pump station data, extract the pump station position, pump station efficiency, total pump power, and total pump head of each pump station; analyze the pump station data and drainage well data to determine the flow path length and flow path diameter between each pump station and the 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, determine the pump station regulation capacity of each pump station for each drainage well connected to it at a specified fluid velocity; take the sum of the self-drainage capacity and the pump station regulation capacity as the drainage capacity of the corresponding drainage well, and construct a directed graph of the drainage pipe network according to the drainage well position, pump station position, and drainage capacity, and use the directed graph of the drainage pipe network as the drainage pipe network model.

[0072] The drainage well position can be the coordinate position of each drainage well in the corresponding urban area. The drainage well diameter can be the designed wellhead diameter of each drainage well. The drainage well vertical depth can be the length of the vertical part of the drainage well leading to the ground. The drainage path length can be the length of the connecting pipeline path between the drainage well and the main drainage trunk road. The self-drainage capacity evaluation model can be a mathematical model for quantifying the self-drainage capacity of the drainage well.

[0073] The specified fluid velocity can be the flow velocity of the sewage discharged in the drainage well in the drainage well. The self-drainage capacity can be the drainage capacity of the drainage well itself without the intervention of other auxiliary facilities. The pump station position can be the coordinate position of each pump station in the corresponding urban area. The pump station efficiency can be the ratio of the actual output mechanical energy to the input energy during the operation of the pump station. The total pump power can be the total power required during the operation of the pump station, usually including the input power of the pump and the power required by other auxiliary equipment.

[0074] The total head of the pumping station can be the total height of the head that the pumping station can overcome, reflecting the lifting capacity of the pumping station.

[0075] The length of the flow path can be the length of the connecting pipe between each drainage well and its corresponding pumping station.

[0076] The diameter of the flow path can be the diameter of the connecting pipe between each drainage well and its corresponding pumping station.

[0077] The regulation capacity of the pumping station can be the auxiliary capacity of the pumping station for the drainage capacity of each drainage well connected to it.

[0078] The directed graph of the drainage pipe network can be the directed graph data representing the connection relationship characteristics between each drainage well and the pumping station and the corresponding drainage capacity or regulation capacity.

[0079] Specifically, in the process of evaluating the drainage capacity of the drainage well, it is necessary to comprehensively consider the self-drainage capacity of the drainage well and the regulation capacity of external auxiliary equipment. Among them, the self-drainage capacity of the drainage well is mainly determined by the design structure characteristics of the drainage well itself, mainly including the diameter of the drainage well, the vertical depth of the drainage well, and the length of the drainage path. Through mathematical analysis means, describe the mathematical influence relationship between the diameter of the drainage well, the vertical depth of the drainage well, and the length of the drainage path and the self-drainage capacity of the drainage well, and construct a self-drainage capacity evaluation model to quantify the self-drainage capacity of each drainage well at a specified fluid velocity, providing influence data from the structure of the drainage well itself for the actual drainage capacity analysis of the drainage well.

[0080] The regulation capacity of the external auxiliary equipment mainly depends on the drainage capacity of the pumping station connected to the drainage well. The drainage capacity of the pumping station is mainly affected by the pumping station efficiency, the total pump power, and the total head of the pumping station. On this basis, since each pumping station is usually connected to multiple drainage wells, and there are differences in the connecting paths between each drainage well and the pumping station, therefore, in the process of evaluating the drainage capacity of the drainage well, it is necessary to consider the interaction relationship between the pumping station and the drainage well. Based on the positions of the drainage well, the pumping station, and the corresponding connection relationship, extract the length of the flow path and the diameter of the flow path between each pumping station and the different drainage wells connected to it as the mapping data for the subsequent analysis of the interaction relationship between the pumping station and the drainage well. Through further mathematical analysis means, based on the pumping station efficiency and the total pump power, according to the length of the flow path and the diameter of the flow path, quantify the pumping station regulation capacity of each pumping station for each drainage well connected to it at a specified fluid velocity, providing influence data from the pumping station regulation effect for the actual drainage capacity analysis of the drainage well.

[0081] After determining the self-drainage capacity and the pumping station regulation capacity, the sum of the self-drainage capacity and the pumping station regulation capacity is used as the drainage capacity of the corresponding drainage well. Based on the drainage well location, the pumping station location, and the drainage capacity, the drainage well location and the pumping station location are respectively used as the nodes of a directed graph, the connection 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 connection 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. In this way, a directed graph of the drainage pipe network is constructed, and the directed graph of the drainage pipe network is used as the drainage pipe network model. When there are local changes in the urban drainage pipe network, only the new nodes and paths need to be added to the existing directed graph of the drainage pipe network in the above manner, or the existing directed graph of the drainage pipe network is adjusted according to the changes in the nodes and paths, so as to realize the dynamic update of the drainage pipe network model and ensure the real-time nature of the subsequent ponding state analysis process.

[0082] Through this solution, an evaluation model for the self-drainage capacity is constructed according to the drainage well diameter, the vertical depth of the drainage well, and the length of the drainage path corresponding to the drainage well, so as to evaluate the self-drainage capacity of each drainage well. At the same time, based on the pumping station efficiency and the total pump power, and according to the length of the flow path and the diameter of the flow path, the pumping station regulation capacity of each pumping station for each drainage well connected to it is evaluated. On this basis, the drainage capacity of the drainage well is comprehensively evaluated, and according to the drainage well location, the pumping station location, and the drainage capacity, a directed graph of the drainage pipe network is constructed, and the directed graph of the drainage pipe network is used as the drainage pipe network model, realizing a highly data abstraction process for the urban drainage pipe network. While scientifically evaluating the drainage capacity of the urban drainage pipe network, through the corresponding data structure, the dynamic expansion ability of the drainage pipe network model is improved, and the real-time nature of the subsequent ponding state analysis process is ensured.

[0083] In some embodiments, an evaluation model for the self-drainage capacity of each drainage well is constructed according to the drainage well diameter, the vertical depth of the drainage well, and the length of the drainage path, and the self-drainage capacity of each drainage well at a specified fluid velocity is determined thereby, specifically as the following formula (1):

[0084] (1)

[0085] Where, is the self-drainage capacity of the th drainage well, is the drainage well diameter of the th drainage well, is the th drainage well, is the preset path friction coefficient, is the th drainage well, is the acceleration due to gravity, is the The vertical depth of a drainage well.

[0086] The preset path friction coefficient can be a value used to characterize the pressure loss caused by friction when fluid flows in a drainage pipe. The preset path friction coefficient is determined by the drainage pipe material and can be obtained through data fitting of the drainage pipe.

[0087] Specifically, through the in formula (1) describes the fluid flow rate in the drainage well at the current fluid velocity. The fluid flow rate is positively correlated with the self-draining capacity of the drainage well. Furthermore, through quantifies the head loss caused by the combined effects of friction loss and height drop of the fluid in the drainage well. Finally, formula (5) scientifically quantifies the self-draining capacity of each drainage well to accurately measure the drainage capacity of the drainage well under the influence of its own design structure.

[0088] Through this solution, by using mathematical analysis means, based on the diameter of the drainage well, the vertical depth of the drainage well, and the length of the drainage path, a self-draining capacity evaluation model is constructed using mathematical language to describe the influence of the above factors on the self-draining capacity of the drainage well. And according to the self-draining capacity evaluation model, the self-draining capacity of each drainage well is scientifically quantified to accurately measure the drainage capacity of the drainage well under the influence of its own design structure, providing a solid data basis for the subsequent analysis of the actual drainage capacity of the drainage well.

[0089] In some embodiments, based on the pump station efficiency and the total pump power, according to the length of the flow path and the diameter of the flow path, the pump station regulation capacity of each pump station for each drainage well connected to it at a specified fluid velocity is determined, specifically as formula (2) below:

[0090] (2)

[0091] Where is the pump station regulation capacity of the th pump station for the th drainage well connected to it, is the pump station efficiency, is the total pump power, is the preset average fluid density, is the total head of the pump station, is the preset path friction coefficient, is the th pump station to the th drainage well, is the th pump station to the th drainage well, the The diameter of the flow path between the th pumping station and the

[0092] The preset average fluid density can be the average fluid density of the fluid discharged in the drainage pipeline, and the preset average fluid density can be obtained by fitting historical water body detection data.

[0093] Specifically, through the in formula (2) to quantify the head loss caused by frictional loss of the fluid in the flow path. In this process, the diameter of the flow path is introduced to further improve the dynamic characteristics of the fluid in the flow path, that is, the larger the pipe diameter, the relatively smaller the frictional loss at the same flow velocity. Through describe the effective head, and then through describe the overall gravitational potential energy of the fluid in the flow path, and at the same time through quantify the output power of the pumping station. The ratio of the output power of the pumping station to the overall gravitational potential energy of the fluid reflects the ability of the current pumping station to pump the fluid in cooperation with the current drainage well, so as to quantify the regulation ability of the pumping station.

[0094] Through this solution, by using mathematical analysis means, based on the pumping station efficiency and the total pump power, according to the length of the flow path and the diameter of the flow path, the influence of the above-mentioned parameters on the regulation ability of the pumping station is clarified in mathematical language, so as to quantitatively obtain the regulation ability of each pumping station to each drainage well connected to it at a specified fluid velocity, and then clarify the influence of the pumping station on the drainage ability of the drainage well connected to it, further improving the accuracy and scientificity of the analysis process of the actual drainage ability of the drainage well.

[0095] In some embodiments, according to the terrain elevation data and the facility location data, determine the relative terrain height of the location of each key facility; based on the facility type data, analyze the facility coverage area data to determine the redundancy index and the facility importance level of each key facility; analyze the facility structure data to determine the facility waterproof index of each key facility; according to the relative terrain height, the redundancy index, the facility importance level and the facility structure data, determine the waterlogging sensitivity of each key facility; according to the facility location data and the waterlogging sensitivity, perform sensitivity marking on each key facility; perform unified spatial mapping processing on the terrain elevation data and the facility location data after the marking is completed to construct a regional basic model.

[0096] The terrain parameter set includes terrain elevation data.

[0097] The key facility parameter set includes facility location data, facility type data, facility structure data and facility coverage area data.

[0098] The terrain elevation data can be digital information describing the undulating terrain in the current urban area.

[0099] The facility location data may be the location coordinate data of a key facility within the current urban area.

[0100] The relative terrain height is the relative height of the terrain corresponding to the location where the key facility is located within the current urban area.

[0101] The facility type data may be the data used to characterize the type to which the key facility belongs.

[0102] The facility structure data may be the design structure parameters corresponding to the key facility.

[0103] The facility coverage area data may be the area information covered by the corresponding function of the key facility.

[0104] The redundancy index may be a numerical value used to characterize the degree of redundancy design of the key facility.

[0105] The facility importance level may be the information used to characterize the importance degree of the key facility within the current urban area.

[0106] The facility waterproof index may be a numerical value used to characterize the degree of waterproof design of the key facility.

[0107] The waterlogging sensitivity may be a quantitative numerical value used to characterize whether the key facility is vulnerable to waterlogging. The higher the waterlogging sensitivity, the more easily the current key facility is affected by waterlogging.

[0108] Specifically, there is a wide variety of key facilities located within urban areas, and they are widely distributed. Different types of key facilities located in different positions are significantly different in terms of the degree of impact they receive from accumulated water during urban waterlogging. After being affected by accumulated water, there are also differences in the scope of influence spread by the anomalies of key facilities. 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 where the key facilities are located, the less likely they are to be affected. Based on the information corresponding to the facility location data in the terrain elevation data, the relative terrain height of the key facilities can be determined. Secondly, it is affected by the redundant design of key facilities and the importance level of the facilities. If a key facility has more redundant designs, it means that even if some structures of the current key facility are affected by accumulated water, it can still maintain a normal state relying on the redundant design. Then, this key facility is less likely to be affected by accumulated water. The redundant design can be reflected by the redundancy index evaluated during the design stage of the key facility. The importance level of the facilities directly affects the severity of the consequences caused after the key facilities are affected by accumulated water. The higher the importance level of the key facilities, the more serious the consequences after they are affected by accumulated water. The importance level of the facilities is directly affected by the facility type and the coverage area of the facilities. The facility type determines the absolute importance level of the key facilities. The corresponding importance levels of different types of key facilities can be set according to the expert evaluation results. The coverage area of the facilities determines the scope of the consequences spread after the key facilities are damaged by accumulated water. Whether a key facility is easily affected by accumulated water is also affected by the waterproof index of the facility reflected in the facility structure data corresponding to the key facility itself. The higher the waterproof index, the more sufficient waterproof measures have been taken during the construction stage of this key facility, and the less likely this key facility is to be affected by accumulated water.

[0109] Therefore, through mathematical analysis methods, based on the relative terrain height, redundancy index, importance level of the facilities, facility structure data, and waterproof index of the facility, comprehensively quantify the waterlogging sensitivity corresponding to the key facilities to reflect the sensitivity of the key facilities to the impact of waterlogging under the influence of their location and their own state, providing a scientific basis for subsequent quantification of the multi-dimensional risks caused by waterlogging. After determining the waterlogging sensitivity, according to the facility location data and the waterlogging sensitivity, mark the sensitivity of each key facility, and perform unified spatial mapping processing on the terrain elevation data and facility location data after the marking is completed to achieve effective integration of the terrain data and key facility data, avoiding the situation of misalignment deviation between the terrain data and the key data, and thus constructing an accurate regional basic model.

[0110] Through this solution, based on the relative terrain height, redundancy index, facility importance level, facility structure data, and facility waterproof index, a targeted analysis is conducted on the waterlogging sensitivity of different types of key facilities at their respective locations, so as to scientifically reflect the sensitivity of different key facilities to the impact of waterlogging, provide a scientific basis for subsequent quantification of the multi-dimensional risks caused by waterlogging, and perform unified spatial mapping processing on the terrain elevation data and facility location data after annotation to construct a regional basic model, avoiding the situation of misalignment deviation between terrain data and key data, and improving the accuracy and data consistency of the regional basic model.

[0111] In some embodiments, based on the relative terrain height, redundancy index, facility importance level, facility structure data, and facility waterproof index, the waterlogging sensitivity of each key facility is determined, specifically as the following formula (3):

[0112] (4)

[0113] Wherein, is the waterlogging sensitivity, is the facility importance level, is the preset amplification 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 attenuation index.

[0114] The preset amplification index can be a quantitative value used to adjust the influence of the facility importance level on the waterlogging sensitivity, and the preset amplification index can be obtained by fitting historical waterlogging data.

[0115] The preset adjustment coefficient can be a quantitative value used to adjust the influence of the facility waterproof index on the waterlogging sensitivity, and the preset adjustment coefficient can be obtained by fitting historical waterlogging data.

[0116] The preset redundancy influence coefficient can be a value used to reflect the linear relationship between the redundancy index and the waterlogging sensitivity, and the preset redundancy influence coefficient can be obtained by fitting historical waterlogging data.

[0117] The preset attenuation index can be a quantitative value used to adjust the attenuation characteristics of the influence of the relative terrain height on the waterlogging sensitivity, and the preset redundancy influence coefficient can be obtained by fitting historical waterlogging data.

[0118] Specifically, through in formula (4) reflects the non-linear positive correlation relationship between the facility importance level and the waterlogging sensitivity; through reflects the inverse proportional relationship between the facility waterproof index and the waterlogging sensitivity, and through Adjust the influence degree; by Reflect the complex influence of the redundancy index on the waterlogging sensitivity. Using a logarithmic function can prevent the sharp decline of waterlogging sensitivity caused by a high redundancy index and ensure that the influence of the redundancy index on waterlogging sensitivity shows a decreasing effect; by Reflect the direct influence of the relative terrain height on the waterlogging sensitivity. The higher the relative terrain, the lower the waterlogging sensitivity, by Control the influence degree of the relative terrain height on the waterlogging sensitivity; comprehensively consider the above influences and scientifically quantify the waterlogging sensitivity of key facilities.

[0119] Through this solution, by using mathematical analysis methods, based on the relative terrain height, redundancy index, facility importance level, facility structure data, and facility waterproof index, through clear mathematical relationships, accurately quantify the waterlogging sensitivity of key facilities, improve the scientificity and comprehensiveness of the waterlogging sensitivity analysis process, and further improve the accuracy of the subsequent waterlogging risk analysis process based on waterlogging sensitivity.

[0120] In some embodiments, based on the flow velocity information, according to the drainage network model, determine the real-time drainage capacity of each drainage well; according to the water collection information, extract the water collection area of each drainage well; according to the regional basic model, determine the surface elevation of the well point of each drainage well; according to the real-time rainfall, real-time drainage capacity, and water collection area, determine the real-time runoff volume corresponding to each drainage well, and thus determine the total runoff volume; according to the real-time rainfall, total runoff volume, real-time drainage capacity, and surface elevation of the well point, construct a water level change evaluation model to evaluate the real-time waterlogging level; based on the water level change evaluation model and rainfall change information, according to the hydrodynamic equation, update the real-time waterlogging level; based on the regional basic model, analyze the real-time waterlogging level, determine the waterlogging risk information corresponding to different key facilities, and thus determine the multi-dimensional risk information set.

[0121] The meteorological parameter set includes real-time rainfall, rainfall change information, water collection information, and flow velocity information.

[0122] The real-time rainfall can be the rainfall corresponding to the current analysis time point.

[0123] The rainfall change information can be the information on the change of rainfall over time.

[0124] The water collection information can be the surface waterlogging collection information in the current urban area.

[0125] The flow velocity information can be the water flow velocity information in each drainage well.

[0126] The real-time drainage capacity can be the actual drainage capacity corresponding to each drainage at the current analysis time point.

[0127] The catchment area can be the surface water collection area within the current analysis area.

[0128] The ground elevation of the well point can be the elevation data corresponding to the position of the wellhead of the drainage well.

[0129] The real-time runoff can be the surface water flow information within the current analysis area.

[0130] The water level change evaluation model can be a mathematical model used to characterize the characteristics of the water level of the accumulated water changing with time within the current analysis area.

[0131] The real-time accumulated water level can be the height of the surface water level of the accumulated water within the current analysis area.

[0132] The accumulated water risk information can be the risk of the key facilities being affected under the current accumulated water state.

[0133] Specifically, after constructing the drainage pipe network model and the regional basic model in the manner of the foregoing embodiments, the accumulated water flow velocity in each drainage well reflected in the flow velocity information is input into the drainage pipe network model, and the real-time drainage capacity of each drainage well is quantified. The catchment area within the area where each drainage well is located in the catchment information reflects the state of surface runoff collection at the wellhead of the drainage well. The change of surface runoff directly affects the change state of the accumulated water in this area. According to the product of the real-time rainfall and the catchment area, the runoff volume at the wellhead of the drainage well is estimated. Combining with the real-time drainage capacity of the drainage well, the real-time runoff volume at each wellhead is estimated, and by integrating the real-time runoff volumes of each drainage well in the area corresponding to the current catchment area, the total runoff volume of the current catchment area is determined. Through mathematical analysis means, according to the real-time rainfall, total runoff volume, real-time drainage capacity and the ground elevation of the well point, a water level change evaluation model is constructed. By solving the water level change evaluation model, the real-time accumulated water level is evaluated, and based on the rainfall change information, according to the hydrodynamic equation, the change of the accumulated water level caused by the rainfall change in the regional basic model is tracked to realize the update of the real-time accumulated water level, which is used as the dynamic data basis for determining the accumulated water risk information corresponding to different key facilities to construct a multi-dimensional risk information set.

[0134] Through this solution, based on the meteorological parameter set, according to the drainage pipe network model and the regional basic model, under the dynamic precipitation change, under the combined influence of the drainage pipe network model and the regional basic model, the development trend of the accumulated water is simulated, a water level change evaluation model is constructed to evaluate the real-time accumulated water level in the area, and at the same time, combined with the hydrodynamic equation, the real-time accumulated water level is dynamically updated to realize the tracking of the change of the real-time accumulated water level, which is used as the dynamic data basis for determining the accumulated water risk information corresponding to different key facilities to construct a multi-dimensional risk information set, significantly improving the accuracy and real-time performance of the multi-dimensional risk judgment.

[0135] 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 as the following formula (5):

[0136] (5)

[0137] Wherein, is the real-time ponding water level, is the total runoff, is the real-time rainfall, is the preset time step, is the th real-time drainage capacity of the drainage well, is the indicator function, is the th well point surface elevation of the drainage well; The hydrodynamic equation is specifically the following formula (6):

[0138] (6)

[0139] Wherein, is the total runoff, is the runoff velocity vector, is the acceleration of gravity, is the real-time ponding water level, is the terrain elevation gradient.

[0140] The preset time step can be the preset interval time step for evaluating the real-time water level, and the preset time step can be set according to specific analysis requirements.

[0141] The runoff velocity vector can be vector information used to characterize the velocity and direction of the accumulated water flow, and the runoff velocity vector can be derived according to the accumulated water flow velocity using the fluid continuity equation.

[0142] The terrain elevation gradient can be quantitative information reflecting the characteristics of terrain elevation changes, and the terrain elevation gradient can be obtained by gradient extraction of the terrain elevation data using the spatial difference algorithm based on the terrain elevation data.

[0143] The indicator function can be a function used to characterize and feedback whether the function content holds. For example, represents that when , the function feedback data is 1, and when , the function feedback data is 0.

[0144] Specifically, the rainfall contribution within the preset time step is described by in formula (5); The drainage volume is determined by the drainage capacity and water level relationship of each drainage well. Only when the water level is higher than the wellhead does the concept of accumulated water drainage hold, which is expressed as , for evaluating the drainage volume of accumulated water; according to the principle of mass conservation, the increase in the accumulated water level minus the water volume discharged from the drainage well is equal to the change in rainfall per unit time, which is formally expressed as: , substituting the aforementioned rainfall contribution and accumulated water drainage volume into the above formal expression, a water level change evaluation model corresponding to formula (5) is constructed. Further, based on momentum and mass conservation, a hydrodynamic equation corresponding to formula (6) is constructed, where is used to describe the change of accumulated water flow per unit volume over time and the effect of water flow velocity, is used to describe the gravitational effect caused by the change of the real-time accumulated water level in its corresponding terrain.

[0145] Through this solution, by using mathematical analysis means, based on the real-time rainfall, total runoff, real-time drainage capacity and well point surface elevation, a water level change evaluation model is constructed through clear mathematical relationships to realize the evaluation of the real-time accumulated water level. Combining with the hydrodynamic equation, the dynamic update of the real-time accumulated water level is realized, providing scientific support for the determination of the real-time accumulated water level, improving the accuracy of the judgment of the real-time accumulated water level, and further improving the accuracy of multi-dimensional risk judgment based on the real-time accumulated water level.

[0146] In some embodiments, according to the regional basic model, a number of key facilities within the water accumulation area are determined; based on the real-time accumulated water level, according to the water accumulation sensitivity corresponding to the number of key facilities, the real-time water accumulation risk corresponding to each key facility is determined; according to the real-time water accumulation risk corresponding to each key facility and the facility coverage area data, the water accumulation risk information corresponding to the key facility is constructed, thereby determining the multi-dimensional risk information set.

[0147] Specifically, according to the real-time accumulated water level, analyze the parameters of each key facility corresponding in the regional basic model, and screen out a number of key facilities that will be affected by the real-time accumulated water level in the current water accumulation area. Further, combined with the water accumulation sensitivity corresponding to the number of key facilities, determine the water accumulation risk information shown by the above-mentioned number of key facilities under the influence of their water accumulation sensitivity at the current real-time accumulated water level. The risk establishment rule is: according to the real-time accumulated water level, determine the basic water accumulation risk of the above-mentioned number of key facilities. The basic water accumulation risk can be obtained by multiplying the relationship coefficient between the accumulated water level and the basic water accumulation risk obtained by fitting historical accumulated water data and the real-time accumulated water level, and obtain the water accumulation risk information of the key facility by multiplying the basic water accumulation risk by the water accumulation sensitivity of the corresponding key facility. By integrating the water accumulation risk information of different key facilities and combining the facility coverage area data corresponding to the above-mentioned number of key facilities, a multi-dimensional risk information set is obtained. The facility coverage area data can assist the corresponding positioning technology, such as cellular network positioning technology, in accurately delimiting the different risk influence ranges during the water accumulation warning process, and further assist in determining different target users within different risk influence ranges.

[0148] Through this solution, based on the real-time waterlogging level, key facilities affected under the current waterlogging state are screened, and combined with the waterlogging sensitivity corresponding to the key facilities, the real-time waterlogging risk of the key facilities is evaluated. Further, the data of the facility coverage area corresponding to the key facilities is integrated to obtain the waterlogging risk information corresponding to the key facilities, and a multi-dimensional risk information set is constructed based on this, which helps to accurately delimit different risk impact ranges and further helps to determine different target users within different risk impact ranges, improving the pertinence and accuracy of the push of waterlogging warning information.

[0149] Figure 3 FIG. is a schematic structural diagram of a waterlogging warning system based on urban waterlogging simulation positioning provided by an embodiment of the present application, as Figure 3 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.

[0150] The pipe network analysis module 301 is configured to obtain a 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 configured 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; the risk analysis module 303 is configured to obtain a meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, according to the regional basic model, simulate the development trend of waterlogging, and thereby determine a multi-dimensional risk information set; the warning module 304 is configured to, based on the regional basic model, according to the multi-dimensional risk information set, determine target push users and corresponding warning push information, and push the warning push information to the target push users.

[0151] Optionally, the pipe network analysis module 301 is specifically configured to: extract the drainage well location, drainage well diameter, drainage well vertical depth, and drainage path length corresponding to each drainage well according to the drainage well data; construct an evaluation model for the self-drainage capacity of each drainage well based on 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 location, pump station efficiency, total pump power, and total pump head of each pump station according to the pump station data; analyze 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; based on the pump station efficiency and the total pump power, determine the 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; use the sum of the self-drainage capacity and the pump station regulation capacity as the drainage capacity of the corresponding drainage well, and construct a directed graph of the drainage pipe network according to the drainage well location, the pump station location, and the drainage capacity, and use the directed graph of the drainage pipe network as the drainage pipe network model.

[0152] Optionally, when the pipe network analysis module 301 constructs an evaluation model for the self-drainage capacity of each drainage well based on the drainage well diameter, the drainage well vertical depth, and the drainage path length, and thereby determines the self-drainage capacity of each drainage well at a specified fluid velocity, the specific formula is as follows:

[0153] ;

[0154] Wherein, is the self-drainage capacity of the th drainage well, is the drainage well diameter of the th drainage well, is the fluid velocity in the th drainage well, is the preset path friction coefficient, is the drainage path length of the th drainage well, is the acceleration of gravity, is the drainage well vertical depth of the th drainage well.

[0155] Optionally, when 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, the specific formula is as follows:

[0156] ;

[0157] Among them, is the th pumping station's regulation capacity for the th drainage well connected to it, is the efficiency of the pumping station, is the total pump power, is the total head of the pumping station, is the preset path friction coefficient, is the th pumping station to the th drainage well's length of the flow path therebetween, is the th pumping station to the th drainage well's fluid velocity in the flow path therebetween, The th pumping station to the th drainage well's diameter of the flow path therebetween.

[0158] Optionally, the area analysis module 302 is specifically configured to: determine the relative terrain height of the location of each key facility according to 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 the facility importance level of each key facility; analyze the facility structure data to determine the facility waterproof index of each key facility; determine the waterlogging 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; perform sensitivity marking on each key facility according to the facility location data and the waterlogging sensitivity; perform unified spatial mapping processing on the terrain elevation data and the facility location data after the marking is completed to construct the area basic model.

[0159] Optionally, when the area analysis module 302 determines the waterlogging 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: ; where is the waterlogging sensitivity, is the facility importance level, is the preset amplification 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 attenuation index.

[0160] Optionally, the risk analysis module 303 is specifically configured to: based on the flow velocity information, determine the real-time drainage capacity of each drainage well according to the drainage pipe network model; extract the catchment area of each drainage well according to the catchment information; determine the ground elevation of the well point of each drainage well according to the regional basic model; determine the real-time runoff volume corresponding to each drainage well based on the real-time rainfall, the real-time drainage capacity and the catchment area, so as to determine the total runoff volume; construct a water level change evaluation model based on the real-time rainfall, the total runoff volume, the real-time drainage capacity and the ground elevation of the well point to evaluate the real-time waterlogging level; update the real-time waterlogging level according to the water flow dynamics equation based on the water level change evaluation model and the rainfall change information; analyze the real-time waterlogging level based on the regional basic model, determine the waterlogging risk information corresponding to different key facilities, so as to determine the multi-dimensional risk information set.

[0161] Optionally, when the risk analysis module 303 constructs a water level change evaluation model according to the real-time rainfall, the total runoff volume, the real-time drainage capacity and the ground elevation of the well point, it is specifically the following formula: ;

[0162] Wherein, is the real-time waterlogging level, is the total runoff volume, is the real-time rainfall, is the preset time step, is the real-time drainage capacity of the th drainage well, is the indicator function, is the ground elevation of the well point of the th drainage well; the water flow dynamics equation is specifically the following formula: ; wherein, is the total runoff volume, is the runoff velocity vector, is the real-time waterlogging level, is the terrain elevation gradient.

[0163] Optionally, when the risk analysis module 303 analyzes the real-time waterlogging level based on the regional basic model to determine the waterlogging risk information corresponding to different key facilities, so as to determine the multi-dimensional risk information set, it is specifically used for: determining several key facilities located in the waterlogging area according to the regional basic model; based on the real-time waterlogging level, determining the real-time waterlogging risk corresponding to each key facility according to the waterlogging sensitivity corresponding to the several key facilities; constructing the waterlogging risk information corresponding to the key facility according to the real-time waterlogging risk corresponding to each key facility and the facility coverage area data, so as to determine the multi-dimensional risk information set.

[0164] The system of this embodiment can be used to execute the method of any of the above embodiments, and its implementation principle and technical effect are similar, which will not be elaborated here.

Claims

1. A waterlogging warning method based on urban waterlogging simulation and positioning, characterized in that Including: Obtain a regional pipe network parameter set, analyze the regional pipe network parameter set, and construct a drainage pipe network model; 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; Obtain a meteorological parameter set, based on the meteorological parameter set and the drainage pipe network model, according to the regional basic model, simulate the development trend of waterlogging, and thereby determine a multi-dimensional risk information set; Based on the regional basic model, according to the multi-dimensional risk information set, determine the target push users and the corresponding early warning push information, and push the early warning push information to the target push users; The terrain parameter set includes terrain elevation data, and the key facility parameter set includes facility location data, facility type data, facility structure data, and facility coverage area data. 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, determine the relative terrain height of the location where each key facility is located; Based on the facility type data, analyze the facility coverage area data to determine the redundancy index and the facility importance level of each key facility; Analyze the facility structure data 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, determine the waterlogging sensitivity of each key facility; According to the facility location data and the waterlogging sensitivity, perform sensitivity marking on each key facility; Perform unified spatial mapping processing on the terrain elevation data and the facility location data after the marking is completed to construct the regional basic model.

2. The method according to claim 1, wherein The pipe network parameter set includes drainage well data and pumping station data. Analyzing the regional pipe network parameter set to construct a drainage pipe network model includes: According to the drainage well data, extract the drainage well location, drainage well diameter, drainage well vertical depth, and drainage path length corresponding to each drainage well; According to the drainage well diameter, the drainage well vertical depth, and the drainage path length, construct an evaluation model for the self-drainage capacity of each drainage well, and thereby determine the self-drainage capacity of each drainage well at a specified fluid velocity; According to the pumping station data, extract the pumping station location, pumping station efficiency, total pump power, and total pumping head of each pumping station; Analyze the pumping station data and the drainage well data to determine the flow path length and flow path diameter between each pumping station and different drainage wells connected to it; Based on the pumping station efficiency and the total pump power, according to the flow path length and the flow path diameter, determine the pumping station regulation ability of each pumping station for each drainage well connected to it at a specified fluid velocity; Take the sum of the self-drainage capacity and the pumping station regulation ability as the drainage capacity of the corresponding drainage well. According to the drainage well location, the pumping station location, and the drainage capacity, construct a directed graph of the drainage pipe network, and use the directed graph of the drainage pipe network as the drainage pipe network model.

3. The method according to claim 2, wherein Construct an evaluation model for the self-draining capacity of each drainage well according to the diameter of the drainage well, the vertical depth of the drainage well, and the length of the drainage path, and determine the self-draining capacity of each drainage well at a specified fluid velocity based on this. Specifically, the formula is as follows: ； Among them, is the self-drainage capacity of the th drainage well, is the diameter of the th drainage well, is the fluid velocity in the th drainage well, is the preset path friction coefficient, is the drainage path length of the th drainage well, is the acceleration of gravity, is the vertical depth of the th drainage well.

4. The method according to claim 2, wherein Based on the pump station efficiency and the total pump power, determine the pump station regulation capacity of each pump station for each drainage well connected to it at a specified fluid velocity according to the length of the flow path and the diameter of the flow path. Specifically, the formula is as follows: ； Among them, is the regulation capacity of the th pumping station for the th drainage well connected to it, is the efficiency of the pumping station, is the total pump power, is the total head of the pumping station, is the preset path friction coefficient, is the th pumping station to the th drainage well, the length of the flow path therebetween, is the th pumping station to the th drainage well, the fluid velocity in the flow path therebetween, the th pumping station to the th drainage well, the diameter of the flow path therebetween.

5. The method according to claim 2, wherein Determine the waterlogging sensitivity of each key facility according to the relative terrain height, the redundancy index, the importance level of the facility, the facility structure data, and the facility waterproof index. Specifically, the formula is as follows: ； wherein, is the waterlogging sensitivity, is the importance level of the facility, is the preset amplification 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 attenuation index.

6. The method according to claim 2, wherein The meteorological parameter set includes real-time rainfall, rainfall change information, water collection information, and flow velocity information. Based on the meteorological parameter set and the drainage network model, simulate the development trend of waterlogging according to the regional basic model, and determine the multi-dimensional risk information set based on this, including: Based on the flow velocity information, determine the real-time drainage capacity of each drainage well according to the drainage network model; Extract the water collection area of each drainage well according to the water collection information; Determine the ground elevation of the well point of each drainage well according to the regional basic model; Determine the real-time runoff volume corresponding to each drainage well according to the real-time rainfall, the real-time drainage capacity, and the water collection area, and determine the total runoff volume based on this; Construct a water level change evaluation model according to the real-time rainfall, the total runoff volume, the real-time drainage capacity, and the ground elevation of the well point to evaluate the real-time waterlogging level; Based on the water level change evaluation model and the rainfall change information, update the real-time waterlogging level according to the hydrodynamic equation; Based on the regional basic model, analyze the real-time waterlogging level, determine the waterlogging risk information corresponding to different key facilities, and determine the multi-dimensional risk information set based on this; 7. The method according to claim 6, characterized in that, Construct a water level change evaluation model according to the real-time rainfall, the total runoff volume, the real-time drainage capacity, and the ground elevation of the well point. Specifically, the formula is as follows: ； Among them, is the real-time ponding water level, is the total runoff volume, is the real-time rainfall, is the preset time step, is the real-time drainage capacity of the th drainage well, is the indicator function, is the ground elevation of the well point of the th drainage well; The hydrodynamic equation is specifically as follows: ； Wherein, is the total runoff volume, is the runoff velocity vector, is the acceleration due to gravity, is the real-time ponding water level, is the terrain elevation gradient.

8. The method according to claim 6, wherein Based on the regional basic model, analyze the real-time waterlogging level, determine the waterlogging risk information corresponding to different key facilities, and determine the multi-dimensional risk information set based on this, including: Determine several key facilities located in the waterlogging area according to the regional basic model; Based on the real-time waterlogging level, determine the real-time waterlogging risk corresponding to each key facility according to 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, and determine the multi-dimensional risk information set based on this; 9. An accumulated water warning system based on urban waterlogging simulation positioning, characterized in that, Applied to the method according to any one of claims 1-8, including: A pipe network analysis module for obtaining a regional pipe network parameter set, analyzing the regional pipe network parameter set, and constructing a drainage network model; The area 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, according to the regional basic model, simulate the development trend of waterlogging, and thereby determine the multi-dimensional risk information set; The early warning module is used to determine the target push users and the corresponding early warning push information based on the regional basic model and according to the multi-dimensional risk information set, and push the early warning push information to the target push users.

Images