Urban facility waterlogging risk assessment method and device, computer equipment and storage medium

Abstract

The invention discloses an urban facility waterlogging risk assessment method and device, computer equipment and a storage medium, and the method comprises the steps: assessing a facility waterlogging static risk according to a historical waterlogging condition, disaster-bearing body dangerousness and disaster-bearing body vulnerability; evaluating the rainfall risk and the riverway water level risk in real time; and superposing the scores of the facility inland inundation static risk, the rainfall risk and the riverway water level risk to obtain a real-time facility inland inundation dynamic risk. According to the method, the static risk of facility waterlogging is comprehensively evaluated according to disaster risk indexes of historical waterlogging conditions, disaster-bearing body risk degree and vulnerability, and the real-time dynamic risk of facility waterlogging is obtained by combining real-time and forecast rainfall and river water level, so that extremely high safety guarantee requirements in the industry are met.

Description

Technical Field

[0001] The invention relates to a method, a device, a computer device and a storage medium for assessing the risk of waterlogging in urban facilities, and belongs to the field of flood model simulation. Background Art

[0002] Heavy rain and waterlogging disasters are natural disasters caused by excessive rainfall in a short period of time, which leads to the inability to drain water from low-lying areas in a timely manner (Pathak, et al., 2020). While the urbanization process promotes urban economic development, it also increases the risk of heavy rain and waterlogging disasters. If we do not speed up and improve disaster prevention and mitigation measures for waterlogging disasters, it will inevitably bring serious economic losses (Gorry and Scott-Morton, 1971, Mason, et al., 2014).

[0003] The occurrence of urban waterlogging disasters is inevitable, and humans do not yet have the ability to fully compete with waterlogging disasters (Li Biqi, 2020). Faced with the increasingly severe problem of urban waterlogging, a large amount of practical experience has shown that simple flood control and drainage engineering measures are not enough to completely resist waterlogging disasters. Therefore, in the early stage of disaster defense, attention should be paid to the application of non-engineering measures such as urban rainstorm waterlogging disaster risk management, urban rainstorm flood simulation and early warning forecast, so as to avoid or reduce the losses caused by waterlogging disasters. Urban rainstorm waterlogging disaster risk assessment is one of the important non-engineering measures to prevent disasters, reduce disaster risks and losses, and is a basic work for disaster prevention and mitigation. Scientifically carrying out rainstorm waterlogging disaster risk assessment can help relevant departments to carry out targeted flood control project layout and flood control work deployment, generating huge economic and social benefits.

[0004] Foreign research on risk assessment of rainstorm waterlogging disasters began in the 1970s. In 1977, Japan formulated the "Comprehensive Water Control Countermeasures", starting from important river sections, and began to compile flood risk maps, which were gradually promoted nationwide (Zhou Yuehua, et al., 2019). Ricardi et al. proposed to apply a two-dimensional mathematical model to two rivers in the Rosario region of Argentina, and determined the flood risk maps under the flood scenarios of 50-year, 100-year and 500-year in the basin (A., et al., 1997). Since the beginning of the 21st century, foreign research on waterlogging risk assessment has made great progress, with innovations in data analysis, indicator selection and assessment methods, and waterlogging disaster risks have been studied from the global scale to the community scale. Hallegattel et al. examined the relevant characteristics of 136 coastal port cities around the world that affect urban vulnerability, analyzed and evaluated the current and future flood risks of these cities, and put forward adaptation suggestions for strengthening disaster planning measures and improving protection standards (S., et al., 2013). Kokst et al. used highly detailed household data to construct a social vulnerability index based on household units and combined flood hazard, exposure and social vulnerability to conduct regional flood risk assessment (E., et al., 2015).

[0005] China started to study the risk of urban flooding disasters in the mid-1980s, starting with flood storage areas and gradually expanding to towns and watersheds, developing from qualitative description to quantitative analysis. Although it started late, it has developed rapidly. Quan Ruisong introduced the subway system into urban waterlogging risk assessment, took the subway system in the central urban area of ​​Shanghai as the research object, constructed a simplified urban rainstorm waterlogging model, and used the frequency method of waterlogging disaster impact to conduct risk assessment of subway stations in the central urban area of ​​Shanghai (Quan Ruisong, 2012). Zhou Feng et al. improved the analytic hierarchy process by using the order weighted average method and the entropy method to address the shortcomings of the analytic hierarchy process, such as its strong subjectivity and single evaluation results, and established a corresponding waterlogging risk assessment model (Zhou Feng, et al., 2012). Zhang Weiwei et al. conducted a risk assessment analysis of rainstorm disasters from three stages: pre-disaster assessment, real-time assessment during the disaster, and post-disaster investigation and assessment, and constructed a staged dynamic risk assessment model (Zhang Weiwei, et al., 2017).

[0006] In summary, current research at home and abroad focuses on the role of human social activities in the formation of urban flooding risks, and continuously innovates assessment methods, etc., and has achieved certain breadth and depth of research results. However, the methods used generally do not make detailed divisions of risk objects. For example, special facilities in industries such as water conservancy and transportation need to carry out targeted urban flooding risk assessment work to meet the extremely high safety requirements in the industry. Summary of the invention

[0007] In view of this, the present invention provides a method, system, computer equipment and storage medium for assessing the risk of urban facility waterlogging, which comprehensively evaluates the static risk of facility waterlogging based on historical waterlogging conditions, the degree of danger of disaster-bearing bodies, and disaster risk indicators of vulnerability, and combines real-time and predicted rainfall and river water levels to obtain real-time dynamic risk of facility waterlogging, so as to meet the extremely high safety requirements in the industry.

[0008] The first object of the present invention is to provide a method for assessing the risk of waterlogging in urban facilities.

[0009] The second object of the present invention is to provide a device for assessing the risk of waterlogging in urban facilities.

[0010] A third object of the present invention is to provide a computer device.

[0011] A fourth object of the present invention is to provide a storage medium.

[0012] The first object of the present invention can be achieved by adopting the following technical solutions:

[0013] A method for assessing waterlogging risk in urban facilities, the method comprising:

[0014] Assess the static risk of facility flooding based on historical flooding conditions, hazard risk and vulnerability of the hazard-bearing body;

[0015] Real-time assessment of rainfall risk and river level risk;

[0016] The scores of static risk of facility waterlogging, rainfall risk, and river level risk are superimposed to obtain the real-time dynamic risk of facility waterlogging.

[0017] Furthermore, the static risk of waterlogging of facilities is assessed based on historical waterlogging conditions, the hazard of the disaster-bearing body and the vulnerability of the disaster-bearing body, including:

[0018] Determine the scores of historical waterlogging conditions, hazard risk of hazard-bearing bodies, and vulnerability of hazard-bearing bodies as well as their corresponding weights, and add them up to obtain the score of static risk of waterlogging of the facility.

[0019] Furthermore, the historical waterlogging situation includes waterlogging frequency, maximum waterlogging depth and waterlogging improvement evaluation. The score of the historical waterlogging situation is calculated based on the scores of waterlogging frequency and maximum waterlogging depth and corresponding weights, combined with the score of waterlogging improvement evaluation.

[0020] Furthermore, the risk of the disaster-prone body includes the frequency of rainstorms, extreme heavy rainfall, geographical location safety and the source of waterlogging. The score of the risk of the disaster-prone body is calculated based on the scores of the frequency of rainstorms, extreme heavy rainfall, geographical location safety and the source of waterlogging and the corresponding weights.

[0021] Furthermore, the vulnerability of the hazard-prone body includes the safety of the facility location, special terrain and comprehensiveness of protective measures. The score of the vulnerability of the hazard-prone body is calculated based on the scores of the safety of the facility location and special terrain and the corresponding weights, combined with the score of the comprehensiveness of protective measures.

[0022] Furthermore, the rainfall risk is assessed in real time, including:

[0023] Collect data on rainfall and waterlogging depth during historical waterlogging events at the facility;

[0024] A regression analysis was conducted on the rainfall and maximum water depth of historical waterlogging events in the facility, and the correlation equation between rainfall and maximum water depth was obtained;

[0025] Determine the threshold of the corresponding rainfall interval according to the risk level of urban waterlogging depth to determine the corresponding rainfall risk level.

[0026] Furthermore, the river water level risk is assessed in real time, including:

[0027] Relating facilities within the vicinity of a river to the river water level;

[0028] When the river water level reaches the warning level, the associated facility risk is set to high risk;

[0029] When the river water level does not reach the warning level, the associated facility risk is determined as the superposition of the static risk of facility waterlogging and the rainfall risk.

[0030] The second object of the present invention can be achieved by adopting the following technical solutions:

[0031] A device for assessing urban facility waterlogging risk, comprising:

[0032] The first assessment module is used to assess the static risk of facility waterlogging based on historical waterlogging conditions, hazard risk and vulnerability of the hazard-bearing body;

[0033] The second assessment module is used to assess rainfall risk and river water level risk in real time;

[0034] The superposition module is used to superimpose the scores of static risk of facility waterlogging, rainfall risk and river water level risk to obtain the real-time dynamic risk of facility waterlogging.

[0035] The third object of the present invention can be achieved by adopting the following technical solutions:

[0036] A computer device comprises a processor and a memory for storing a program executable by the processor. When the processor executes the program stored in the memory, the above-mentioned urban facility waterlogging risk assessment method is implemented.

[0037] The fourth object of the present invention can be achieved by adopting the following technical solutions:

[0038] A storage medium stores a program, and when the program is executed by a processor, the above-mentioned urban facility waterlogging risk assessment method is implemented.

[0039] The present invention has the following beneficial effects compared with the prior art:

[0040] The present invention comprehensively evaluates the static risk of facility waterlogging based on historical waterlogging conditions, the danger level of disaster-bearing bodies, and disaster risk indicators of vulnerability, and obtains real-time dynamic risk of facility waterlogging in combination with real-time and forecast rainfall and river water levels, so as to meet the extremely high safety requirements in the industry and provide support for the prevention and treatment of waterlogging at subway entrances and underground garages. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0042] Figure 1 This is a simplified flow chart of the urban facility waterlogging risk assessment method according to Example 1 of the present invention.

[0043] Figure 2 This is a detailed flow chart of the urban facility waterlogging risk assessment method according to Example 1 of the present invention.

[0044] Figure 3 This is a correlation diagram between the rainfall and the maximum water depth of a waterlogging event in Example 1 of the present invention.

[0045] Figure 4 This is a structural block diagram of an urban facility waterlogging risk assessment device according to Example 2 of the present invention.

[0046] Figure 5 This is a structural block diagram of a computer device according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0048] Embodiment 1:

[0049] There are 283 subway entrances in Guangzhou and thousands of underground garages. These underground facilities are numerous and important, and are the facilities that need to be protected first in urban waterlogging disasters. In view of the large number, wide distribution and complex underlying surface conditions of subway entrances and underground garages, the use of traditional mathematical models for waterlogging has problems such as difficulty in collecting basic data and historical waterlogging data, large modeling workload, and complex causes of waterlogging. The mechanism is difficult to simulate and forecast, etc. Therefore, this embodiment uses basic data such as rainfall, underlying surface, river network, outer river tide level, subway entrances, underground garages, etc. in Guangzhou to study the causes of waterlogging in facilities (subway entrances, underground garages). At the same time, a facility waterlogging risk assessment model is constructed based on the improved analytic hierarchy process, and an urban facility waterlogging risk assessment method suitable for Guangzhou facilities is proposed. The facility waterlogging risk assessment model is quickly constructed, and high-precision short-term forecast rainfall data is combined to provide waterlogging forecast information for a large range of facilities, providing support for waterlogging prevention and treatment of facilities.

[0050] According to the definition of disaster risk by the United Nations Development Program, risk is the expected loss of life, property and economic life caused by a specific natural disaster in a certain area and a given period of time. This embodiment adopts the expression of "static risk (D) = historical waterlogging situation (F) + hazard of disaster-prone body (H) + vulnerability of disaster-prone body (V)", draws on the previous research results of risk zoning in the Guangdong-Hong Kong-Macao Greater Bay Area, comprehensively considers the climate characteristics of coastal areas and the basic conditions of the study area, and selects ten indicators; a static risk assessment system is constructed based on the relevant data of subway entrances and underground garages, and three indicators such as rainfall and river water level are selected to construct a dynamic risk indicator system for waterlogging by combining static risk indicators, as shown in Table 1 below.

[0051] Table 1 Waterlogging risk assessment indicators

[0052]

[0053] like Figure 1 and Figure 2 As shown, the urban facility waterlogging risk assessment method of this embodiment includes the following steps:

[0054] S201. Assess the static risk of waterlogging in facilities based on historical waterlogging conditions, the hazard level of the disaster-bearing body, and the vulnerability of the disaster-bearing body.

[0055] This embodiment determines the scores of historical waterlogging conditions, the hazard of the disaster-bearing body, and the vulnerability of the disaster-bearing body and the corresponding weights, and adds them up to obtain the score of the static risk of waterlogging in the facility. The specific method is as follows:

[0056] First, normalize the indicator value:

[0057]

[0058] After normalization, the maximum value of each factor is 1, the minimum value is 0, and the remaining values ​​are between 0 and 1. In the above formula, represents the normalized value, x ij represents the jth value of the i-th influencing factor, min{x ij} is the minimum value among the i-th influencing factors, max{x ij} is the maximum value of the i-th influencing factor, where the factors refer to the 10 indicators (frequency of waterlogging, maximum waterlogging depth, etc.) under the three scheme layers of historical waterlogging conditions, hazard of disaster-bearing bodies and vulnerability of disaster-bearing bodies in Table 1.

[0059] The static risk of facility waterlogging is obtained by summing up the scores of historical waterlogging, hazard risk of the hazard-bearing body, and vulnerability of the hazard-bearing body, as well as the corresponding weights:

[0060] D=f(F,H,V)=w f F+w h H+w v V

[0061] Among them, D is the static risk of facility flooding, F is the historical flooding situation, H is the hazard of the disaster-bearing body, V is the vulnerability of the disaster-bearing body, and w f , w h , w v are their respective weights; the static risk of facility waterlogging is obtained by multiplying the historical flood conditions, the hazard of the hazard-bearing body and the vulnerability of the hazard-bearing body by the weights and then adding them together.

[0062] The historical waterlogging situation of this embodiment is mainly used to evaluate the severity of waterlogging that has occurred in the disaster-bearing body, which includes the frequency of waterlogging, the maximum waterlogging depth and waterlogging improvement evaluation, as shown in Table 2 below.

[0063] Table 2 Evaluation index system of historical flood situation

[0064]

[0065] This embodiment calculates the score of historical waterlogging conditions based on the scores of waterlogging frequency and maximum waterlogging depth and the corresponding weights, combined with the score of waterlogging improvement evaluation, that is, historical waterlogging condition score = (flooding frequency*weight+maximum waterlogging depth*weight)*flood improvement evaluation.

[0066] The hazards of the disaster-prone body in this embodiment are mainly analyzed from two aspects: 1) Identification of the hazards of disaster-causing factors, that is, determining the probability, location, scope, intensity and duration of disasters within a specific time and space range. In general, the intensity of disaster-causing factors is closely related to the probability of their occurrence, and the intensity of disaster-causing factors can also be expressed by the recurrence period corresponding to their occurrence scenarios; 2) Analysis of the disaster-prone environment, that is, analyzing the characteristics of factors that affect the intensity of flood disaster-causing factors in the disaster-prone environment, such as terrain, water system, underlying surface properties, slope, elevation and other factors; The hazards of the disaster-prone body include the frequency of rainstorms, extreme heavy rainfall and the safety of the geographical location (mainly the location of the substation), as shown in Table 3 below.

[0067] Table 3 Hazard evaluation index system for hazard-prone bodies

[0068]

[0069] This embodiment calculates the score of the disaster-prone body danger based on the scores of rainstorm frequency, extreme heavy rainfall, geographical location safety, and waterlogging source conditions and the corresponding weights, that is, disaster-prone body danger = rainstorm frequency * weight + extreme heavy rainfall * weight + geographical location safety * weight + waterlogging source conditions * weight.

[0070] Among them, heavy rain: the cumulative rainfall in 1 hour exceeds 16mm; the importance of the impact of different sources of water accumulation: evaluate the importance of the impact of different sources of water accumulation (such as cable trench water inflow, river (tide level) impact, nearby road water collection, groundwater infiltration, upstream reservoir impact, etc.), establish the relationship between each source of water accumulation and substation flooding based on the deep algorithm, and then give a comprehensive evaluation. Cable trench water inflow and nearby road water collection are water inflow channels, and the impact of different sources of water accumulation is superimposed. The impact of river (tide level) = upstream reservoir impact > groundwater infiltration.

[0071] The main contents of the vulnerability analysis of disaster-prone bodies in this embodiment are: 1) Identification of exposed elements in the risk area, identifying the types, quantities, values ​​and distribution characteristics of different exposed disaster-prone bodies in the risk area; 2) Evaluation of the vulnerability of elements in the risk area: combined with the exposure factors of the disaster-prone bodies in the risk area, the vulnerability of the population, buildings, properties and other elements in the risk area to disasters is analyzed and evaluated; the vulnerability of the disaster-prone body includes the safety of the facility location (location of facilities prone to flooding), special terrain (whether the substation has special terrain, that is, the safety of the substation) and the comprehensiveness of protection measures (comprehensiveness of waterlogging protection measures), as shown in Table 4 below.

[0072] Table 4. Vulnerability evaluation index system for disaster-prone bodies

[0073]

[0074] This embodiment calculates the vulnerability score of the disaster-prone body according to the scores of facility location safety and special terrain and the corresponding weights, combined with the score of comprehensiveness of protective measures, that is, disaster-prone body vulnerability = (facility location safety * weight + special terrain * weight) * comprehensiveness of protective measures.

[0075] According to the above content, the static risk of facility waterlogging = historical waterlogging situation * weight + hazard of disaster-prone body * weight + vulnerability of disaster-prone body * weight, as shown in Table 5 below.

[0076] Table 5 Static risk assessment index system for facility waterlogging

[0077]

[0078] The static risk of facility waterlogging is divided into levels: a score of <25 is considered no risk, a score of 25<=score<50 is considered low risk, a score of 50<=score<75 is considered medium risk, and a score of >=75 is considered high risk, as shown in Table 6 below.

[0079] Table 6 Static risk level of facility waterlogging

[0080]

[0081]

[0082] S202. Real-time assessment of rainfall risk and river water level risk.

[0083] (1) Rainfall risk: The evaluation data are the actual rainfall, the short-term forecast for the next 2 hours, and the long-term forecast for 72 hours. First, the rainfall and waterlogging depth of historical waterlogging events are counted. Then, the rainfall and maximum waterlogging depth of historical waterlogging events of the facility are regressed and analyzed to obtain the correlation between rainfall and maximum waterlogging depth, as follows: Figure 3 As shown, finally, the threshold of the corresponding rainfall interval is determined according to the risk level of the waterlogging depth to determine the corresponding rainfall risk level. The risk level of the waterlogging depth in this embodiment is based on the "Guangzhou Urban Waterlogging Grade Classification Standard", which sets two thresholds for the waterlogging level according to the waterlogging depth, of which 0-20cm is a slight impact of waterlogging; 20-40cm is a traffic congestion impact, and >40cm is a traffic paralysis. In this embodiment, 0-20cm is further subdivided into 0-10cm (no risk), 10-20cm (low risk), 20-40cm is considered to be medium risk, and >40cm is considered to be high risk according to actual needs.

[0084] Currently, there are not many recorded waterlogging incidents at subway entrances and underground garages. Therefore, waterlogging incidents at other road monitoring points are temporarily added to the waterlogging database, as shown in Table 7 below.

[0085] Table 7 Rainfall risk levels corresponding to the thresholds of rainfall intervals

[0086]

[0087] Specifically, the calculation method of rainfall risk is as follows:

[0088] 1) Find the frequency threshold interval of rainfall in historical waterlogging events.

[0089] 2) F = S 下 +[(RR 下 )(R 上 -R 下 )]*(F 上 -F 下 )

[0090] Among them, F is the rainfall risk score, R 下 is the lowest score corresponding to the frequency, R is the rainfall of historical waterlogging events, and R 下 is the minimum rainfall in the corresponding frequency threshold interval, R 上 is the maximum rainfall in the corresponding frequency threshold interval, F 下 is the lowest score corresponding to the frequency, F 上 It is the highest score corresponding to the frequency.

[0091] 3) If the rainfall exceeds 90 mm, it will be counted as 100 points.

[0092] Rainfall risk score = (current rainfall risk score + forecast rainfall risk score) / 2

[0093] (2) River water level risk: When the water level of the embankment reaches a certain depth, dangerous situations may occur, and flood control personnel are required to patrol the embankment and check for dangers, and be alert to the water level to prepare for flood control and rescue. The facilities near the river (subway entrances, underground garages) are associated with the river water level. When the river water level reaches the warning level, the risk of the associated facilities is set to high risk. When the river water level does not reach the warning level, the risk of the associated facilities is determined as the superposition of the static risk of waterlogging in the facilities and the rainfall risk.

[0094] Specifically, the calculation method of river water level risk is as follows:

[0095] 1) Find subway entrances and underground garages within 0.5 km of the river, and associate them with the water level of the nearby river;

[0096] 2) When the river water level reaches the warning level, the risks of subway entrances and underground garages are set to high risk; when the river water level exceeds the warning level, the risks of related power facilities (substations) are changed to high risk.

[0097] S203. Superimpose the scores of the static risk of facility waterlogging, rainfall risk, and river water level risk to obtain the real-time dynamic risk of facility waterlogging.

[0098] The dynamic risk assessment method for facility waterlogging in this embodiment is as follows:

[0099] Dynamic risk score of facility waterlogging = static risk score of waterlogging + rainfall risk score + river water level risk score

[0100] The dynamic risk levels of facility waterlogging are shown in Table 8 below.

[0101] Table 8 Dynamic risk level of facility waterlogging

[0102]

[0103] It should be noted that although the method operations of the above embodiments are described in a specific order, this does not require or imply that these operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. On the contrary, the steps depicted can be performed in a different order. Additionally or alternatively, some steps can be omitted, multiple steps can be combined into one step, and / or one step can be decomposed into multiple steps.

[0104] Embodiment 2:

[0105] like Figure 4 As shown, this embodiment provides a device for assessing urban facility waterlogging risk, which includes a first assessment module 401, a second assessment module 402 and a superposition module 403, which are specifically described as follows:

[0106] The first assessment module 401 is used to assess the static risk of waterlogging in the facility based on historical waterlogging conditions, the hazard of the disaster-bearing body and the vulnerability of the disaster-bearing body;

[0107] The second assessment module 402 is used to assess rainfall risk and river water level risk in real time;

[0108] The superposition module 403 is used to superimpose the scores of the static risk of facility waterlogging, the rainfall risk and the river water level risk to obtain the real-time dynamic risk of facility waterlogging.

[0109] The specific implementation of each module in this embodiment can refer to the above-mentioned embodiment 1, which will not be described one by one here; it should be noted that the device provided in this embodiment is only illustrated by the division of the above-mentioned functional modules. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure can be divided into different functional modules to complete all or part of the functions described above.

[0110] Embodiment 3:

[0111] This embodiment provides a computer device, such as Figure 5 As shown, it includes a processor 502, a memory, an input device 503, a display device 504 and a network interface 505 connected through a system bus 501. The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium 506 and an internal memory 507. The non-volatile storage medium 506 stores an operating system, a computer program and a database. The internal memory 507 provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. When the processor 502 executes the computer program stored in the memory, the urban facility waterlogging risk assessment method of the above-mentioned embodiment 1 is implemented as follows:

[0112] Based on historical waterlogging conditions, the hazard risk of disaster-bearing bodies, and the vulnerability of disaster-bearing bodies, the static risk of waterlogging in facilities is assessed; the rainfall risk and river water level risk are assessed in real time; and the scores of the static risk of waterlogging in facilities, rainfall risk, and river water level risk are superimposed to obtain the real-time dynamic risk of waterlogging in facilities.

[0113] Embodiment 4:

[0114] This embodiment provides a storage medium, which is a computer-readable storage medium, storing a computer program. When the computer program is executed by a processor, the urban facility waterlogging risk assessment method of the above embodiment 1 is implemented as follows:

[0115] Based on historical waterlogging conditions, the hazard risk of disaster-bearing bodies, and the vulnerability of disaster-bearing bodies, the static risk of waterlogging in facilities is assessed; the rainfall risk and river water level risk are assessed in real time; and the scores of the static risk of waterlogging in facilities, rainfall risk, and river water level risk are superimposed to obtain the real-time dynamic risk of waterlogging in facilities.

[0116] It should be noted that the computer-readable storage medium of the present embodiment may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0117] In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device, or device. In this embodiment, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate, or transmit a program used by or in combination with an instruction execution system, device, or device. The computer program contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0118] The computer readable storage medium can be written in one or more programming languages ​​or a combination thereof to execute the computer program of the present embodiment, and the programming language includes an object-oriented programming language, such as Java, Python, C++, and also includes a conventional procedural programming language, such as C language or a similar programming language. The program can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect through the Internet).

[0119] To sum up, the present invention comprehensively evaluates the static risk of facility waterlogging based on historical waterlogging conditions, the danger level of disaster-bearing bodies, and disaster risk indicators of vulnerability, and combines real-time and predicted rainfall and river water levels to obtain real-time dynamic risk of facility waterlogging, so as to meet the extremely high safety requirements in the industry and provide support for the prevention and treatment of waterlogging at subway entrances and underground garages.

[0120] The above description is only a preferred embodiment of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention.

Claims

1. A method for assessing the risk of urban facility flooding, characterized in that: The method comprises: Assess the static risk of facility flooding based on historical flooding conditions, hazard risk and vulnerability of the hazard-bearing body; Real-time assessment of rainfall risk and river level risk; The scores of static risk of facility waterlogging, rainfall risk, and river level risk are superimposed to obtain the real-time dynamic risk of facility waterlogging.

2. The urban facility waterlogging risk assessment method according to claim 1, characterized in that: The static risk of waterlogging in facilities is assessed based on historical waterlogging conditions, the hazard of the disaster-bearing body and the vulnerability of the disaster-bearing body, including: Determine the scores of historical waterlogging conditions, hazard risk of hazard-bearing bodies, and vulnerability of hazard-bearing bodies as well as their corresponding weights, and add them up to obtain the score of static risk of waterlogging of the facility.

3. The urban facility waterlogging risk assessment method according to claim 2, characterized in that: The historical waterlogging situation includes the frequency of waterlogging, the maximum waterlogging depth and the waterlogging improvement evaluation. The score of the historical waterlogging situation is calculated based on the scores of the frequency of waterlogging and the maximum waterlogging depth and the corresponding weights, combined with the score of the waterlogging improvement evaluation.

4. The urban facility waterlogging risk assessment method according to claim 2, characterized in that: The risk of the disaster-prone body includes the frequency of rainstorms, extreme heavy rainfall, geographical location safety and the source of waterlogging. The score of the risk of the disaster-prone body is calculated based on the scores of the frequency of rainstorms, extreme heavy rainfall, geographical location safety and the source of waterlogging and the corresponding weights.

5. The urban facility waterlogging risk assessment method according to claim 2, characterized in that: The vulnerability of the hazard-prone body includes the safety of the facility location, special terrain and the comprehensiveness of protective measures. The score of the vulnerability of the hazard-prone body is calculated based on the scores of the safety of the facility location and special terrain and the corresponding weights, combined with the score of the comprehensiveness of protective measures.

6. The urban facility waterlogging risk assessment method according to any one of claims 1 to 5, characterized in that: Real-time assessment of rainfall risk, including: Collect data on rainfall and waterlogging depth during historical waterlogging events at the facility; A regression analysis was conducted on the rainfall and maximum water depth of historical waterlogging events in the facility, and the correlation equation between rainfall and maximum water depth was obtained; Determine the threshold of the corresponding rainfall range according to the risk level of urban waterlogging depth to determine the corresponding rainfall risk level.

7. The urban facility waterlogging risk assessment method according to any one of claims 1 to 5, characterized in that: Real-time assessment of river water level risks, including: Relating facilities within the vicinity of a river to the river water level; When the river water level reaches the warning level, the associated facility risk is set to high risk; When the river water level does not reach the warning level, the associated facility risk is determined as the superposition of the static risk of facility waterlogging and the rainfall risk.

8. A device for assessing the risk of urban flooding, characterized in that: The device comprises: The first assessment module is used to assess the static risk of facility flooding based on historical flooding conditions, hazard risk and vulnerability of the hazard-bearing body; The second assessment module is used to assess rainfall risk and river water level risk in real time; The superposition module is used to superimpose the scores of static risk of facility waterlogging, rainfall risk and river water level risk to obtain the real-time dynamic risk of facility waterlogging.

9. A computer device comprising a processor and a memory for storing a program executable by the processor, characterized in that: When the processor executes the program stored in the memory, the urban facility waterlogging risk assessment method described in any one of claims 1-7 is implemented.

10. A storage medium storing a program, characterized in that: When the program is executed by a processor, the urban facility waterlogging risk assessment method described in any one of claims 1 to 7 is implemented.

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