Urban rainfall flood impact cascade propagation simulation method and system and storage medium

Abstract

The invention provides an urban rainfall flood impact cascade propagation simulation method and system and a storage medium. The method comprises the following steps: constructing an infrastructure network according to urban key infrastructure information; constructing an interdependence matrix according to the infrastructure network, and determining a dependence weight according to the interdependence matrix; determining an initial impact node in the infrastructure network according to the urban meteorological observation data; and inputting the infrastructure network, the node upstream and downstream relationship, the dependency weight and the initial impact node into a cascade propagation simulation model for propagation simulation to obtain an urban rainfall flood impact cascade propagation simulation result. According to the embodiment of the invention, the infrastructure network, the upstream and downstream relationship of the nodes, the dependency weight and the initial impact node are input into the cascade propagation simulation model for propagation simulation, so that cascade simulation of urban rainfall flood impact from local node triggering to range diffusion can be effectively realized; and thus, the accuracy of urban rainfall flood disaster impact propagation simulation is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of disaster simulation, and in particular to a city rain flood impact cascade propagation simulation method and system and a storage medium. BACKGROUND

[0002] With the intensification of global climate change and urbanization, extreme rainfall events occur frequently, leading to urban rainstorm flood disasters in the time and space scales, which are characterized by high frequency, great intensity and wide influence. Urban rain flood disasters not only cause direct casualties and property losses, but also trigger a chain reaction due to the impact on critical infrastructure such as transportation networks, power systems, communication facilities, etc., resulting in greater indirect losses and socio-economic impacts. Therefore, the problem of urban rain flood disaster impact propagation simulation is increasingly valued.

[0003] In the existing urban rain flood disaster impact propagation simulation process, the direct impact of rain flood on urban infrastructure is generally simulated, without considering the cascade effect caused by the initial impact of rain flood and the spatial conduction along the urban infrastructure, thereby reducing the accuracy of urban rain flood disaster impact propagation simulation. SUMMARY

[0004] The purpose of the embodiments of the present application is to provide a city rain flood impact cascade propagation simulation method, system and storage medium to solve the problem of low accuracy of urban rain flood disaster impact propagation simulation in the prior art.

[0005] The embodiments of the present application are implemented as follows: a city rain flood impact cascade propagation simulation method, the method comprising: obtaining city critical infrastructure information and constructing an infrastructure network according to the city critical infrastructure information; constructing a mutual dependence matrix according to the infrastructure network and determining a dependence weight according to the mutual dependence matrix, the dependence weight being used to represent the strength of the dependence relationship between different infrastructure nodes in the infrastructure network; obtaining city meteorological observation data and determining an initial impact node in the infrastructure network according to the city meteorological observation data; obtaining the upstream and downstream relationships of the nodes in the infrastructure network and inputting the infrastructure network, the upstream and downstream relationships of the nodes, the dependence weight and the initial impact node into a cascade propagation simulation model for propagation simulation to obtain a city rain flood impact cascade propagation simulation result.

[0006] Preferably, the infrastructure network, the upstream and downstream relationships of the nodes, the dependence weight and the initial impact node are input into the cascade propagation simulation model for propagation simulation to obtain the city rain flood impact cascade propagation simulation result, comprising: In the cascade propagation simulation model, the upstream node and the downstream node of the infrastructure node are determined according to the upstream and downstream relationship of the node, and the initial impact node is set as the failure node; The impact intensity of the corresponding downstream node of the failure node is calculated according to the dependency weight, and the impact probability is calculated according to the impact intensity; If the impact probability of any infrastructure node is greater than the probability threshold, the infrastructure node is determined as the failure node; Return to execute the step of calculating the impact intensity of the corresponding downstream node of the failure node according to the dependency weight until the cascade propagation simulation model meets the simulation termination condition, and output the propagation path and node state change of the failure node in each time step to obtain the urban rainstorm impact cascade propagation simulation result.

[0007] Preferably, the formula used to calculate the impact intensity of the corresponding downstream node of the failure node according to the dependency weight includes: Wherein, represents the failure node i Impacts its downstream nodes j in the current time step, represents the failure node i and its downstream nodes j The dependency weight between, represents the set of normal nodes in the normal state at the current time step, represents the failure node i and its downstream nodes k The dependency weight between, represents the set of failure nodes.

[0008] Preferably, the formula used to calculate the impact probability according to the impact intensity includes: Wherein, represents the impact probability of the downstream node j in the current time step, represents the impact probability of the downstream node j in the last time step, represents the node in the set of failure nodes.

[0009] Preferably, the infrastructure network is constructed according to the urban critical infrastructure information, including: obtaining a city drainage pipe network and a drainage topology connection relationship in the city critical infrastructure information, and setting a pump station, a manhole and a water outlet in the city drainage pipe network as the infrastructure nodes; In the city drainage pipe network, drainage directed edges between the infrastructure nodes are established according to the drainage topology connection relationship, and a direction of the drainage directed edge represents a rainwater flow direction; obtaining a city traffic network and a traffic topology connection relationship in the city critical infrastructure information, and setting a road intersection and a traffic hub in the city traffic network as the infrastructure nodes; In the city traffic network, traffic directed edges between the infrastructure nodes are established according to the traffic topology connection relationship, and a direction of the traffic directed edge represents a traffic passing direction; obtaining a city power network and a power topology connection relationship in the city critical infrastructure information, and setting a transformer substation, a distribution station and a load point in the city power network as the infrastructure nodes; In the city power network, power directed edges between the infrastructure nodes are established according to the power topology connection relationship, and a direction of the power directed edge represents a power transmission direction; obtaining a service relationship between the city drainage pipe network, the city traffic network and the city power network, and constructing cross-network directed dependency edges between the city drainage pipe network, the city traffic network and the city power network according to the service relationship to obtain the infrastructure network, and a direction of the cross-network directed dependency edge represents a service dependency direction in the service relationship.

[0010] Preferably, constructing cross-network directed dependency edges between the city drainage pipe network, the city traffic network and the city power network according to the service relationship to obtain the infrastructure network, comprises: combining the infrastructure nodes in the city drainage pipe network, the city traffic network and the city power network to obtain node pairs; calculating a spatial Euclidean distance between the infrastructure nodes in the node pairs; if the spatial Euclidean distance is less than or equal to a dependency radius threshold, determining that the infrastructure nodes in the node pairs corresponding to the spatial Euclidean distance exist the service relationship; connecting different infrastructure nodes existing the service relationship according to the service dependency direction to obtain the cross-network directed dependency edges, and combining the cross-network directed dependency edges, the city drainage pipe network, the city traffic network and the city power network to obtain the infrastructure network.

[0011] Preferably, a mutual dependence matrix is constructed according to the infrastructure network, comprising: obtaining pipe drainage capacity and service area between the infrastructure nodes corresponding to the drainage directed edge, and constructing drainage weight of the drainage directed edge according to the pipe drainage capacity and the service area; obtaining traffic flow between the infrastructure nodes corresponding to the traffic directed edge, and constructing traffic weight of the traffic directed edge according to the traffic flow; obtaining line power supply load capacity and upstream and downstream power supply dependence ratio between the infrastructure nodes corresponding to the power directed edge, and constructing power supply weight of the power directed edge according to the line power supply load capacity and the upstream and downstream power supply dependence ratio; constructing dependence weight of the cross-network directed dependence edge according to the spatial Euclidean distance, and constructing the mutual dependence matrix according to the dependence weight, the drainage weight, the traffic weight and the power supply weight.

[0012] Another object of the embodiment of the present application is to provide a city rainstorm impact cascade propagation simulation system, which comprises: a network construction module, configured to obtain city key infrastructure information, and construct an infrastructure network according to the city key infrastructure information; a weight determination module, configured to construct a mutual dependence matrix according to the infrastructure network, and determine dependence weight according to the mutual dependence matrix, wherein the dependence weight is used to represent the strength of dependence relationship between different infrastructure nodes in the infrastructure network; an initial impact module, configured to obtain city meteorological observation data, and determine an initial impact node in the infrastructure network according to the city meteorological observation data; an impact simulation module, configured to obtain upstream and downstream relationship of nodes in the infrastructure network, and input the infrastructure network, the upstream and downstream relationship of nodes, the dependence weight and the initial impact node into a cascade propagation simulation model to perform propagation simulation, so as to obtain city rainstorm impact cascade propagation simulation result.

[0013] Preferably, the impact simulation module is further configured to: in the cascade propagation simulation model, determine upstream node and downstream node of the infrastructure node according to the upstream and downstream relationship of nodes, and set the initial impact node as a failure node; calculate impact strength of the failure node on corresponding downstream node according to the dependence weight, and calculate impact probability according to the impact strength; if the impact probability of any infrastructure node is greater than a probability threshold, determine the infrastructure node as the failure node; Return to execute the step of calculating the impact strength of the corresponding downstream node of the failed node according to the dependence weight until the cascade propagation simulation model meets the simulation termination regulation, output the propagation path and node state change of the failed node in each time step, and obtain the city rain flood impact cascade propagation simulation result.

[0014] The embodiment of the application can effectively construct an infrastructure network by acquiring city key infrastructure information, effectively construct a mutual dependence matrix based on the infrastructure network, effectively determine the strength of the dependence relationship between different infrastructure nodes based on the mutual dependence matrix, effectively determine an initial impact node by acquiring city meteorological observation data, and effectively realize cascade simulation of the process of city rain flood impact from local node triggering to range diffusion by inputting the infrastructure network, node upstream and downstream relationship, dependence weight and initial impact node into a cascade propagation simulation model for propagation simulation, thereby improving the accuracy of city rain flood disaster impact propagation simulation. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a flow chart of the city rain flood impact cascade propagation simulation method provided by the first embodiment of the application; Figure 2 is a structural schematic diagram of the city rain flood impact cascade propagation simulation system provided by the second embodiment of the application; Figure 3 is a structural schematic diagram of the terminal device provided by the third embodiment of the application. DETAILED DESCRIPTION

[0016] In order to make the objectives, technical solutions and advantages of the application clearer, the application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and not to limit the application.

[0017] In order to illustrate the technical solutions of the application, the following specific embodiments are used to illustrate the technical solutions of the application.

[0018] Embodiment One Please refer to Figure 1 is a flow chart of the city rain flood impact cascade propagation simulation method provided by the first embodiment of the application, which can be applied to any device or system. The city rain flood impact cascade propagation simulation method includes the following steps: Step S10, acquiring city key infrastructure information and constructing an infrastructure network according to the city key infrastructure information; The infrastructure network is represented by a multi-layer directed graph model, which is coupled by three types of infrastructure sub-networks of drainage, traffic, and power. Based on the spatial geographic information data in the city critical infrastructure information, the structured expression model of the multi-layer network is constructed by extracting the functional nodes, quantifying the topological connection strength and cross-system dependency relationship, and outputting in the form of mutual dependency matrix, thereby providing a structural basis for the cascade propagation simulation.

[0019] In this step, representative and generally available three types of infrastructure data sets are used as input, such as spatial data, point of interest (POI) data, and point data, including city drainage pipe network, city road network, and city power transmission / distribution station and the topological connection relationship therebetween. The key functional units are extracted as network nodes, and the internal connection relationship and weighted directed graph of each sub-network are constructed.

[0020] Optionally, the infrastructure network is constructed according to the city critical infrastructure information, comprising: The city drainage pipe network and drainage topological connection relationship in the city critical infrastructure information are acquired, and the pump station, inspection well, and water outlet in the city drainage pipe network are set as the infrastructure nodes. The drainage topological connection relationship includes the upstream and downstream position connection relationship among the pump station, inspection well, and water outlet. In the city drainage pipe network, the drainage directed edges among the infrastructure nodes are established according to the drainage topological connection relationship, and the direction of the drainage directed edge represents the rainwater flow direction. The city traffic network and traffic topological connection relationship in the city critical infrastructure information are acquired, and the road intersection and traffic hub in the city traffic network are set as the infrastructure nodes. The traffic topological connection relationship includes the position connection relationship among the road intersection and traffic hub. In the city traffic network, the traffic directed edges among the infrastructure nodes are established according to the traffic topological connection relationship, and the direction of the traffic directed edge represents the traffic passing direction. The city power network and power topological connection relationship in the city critical infrastructure information are acquired, and the transformer station, distribution station, and load point in the city power network are set as the infrastructure nodes. The power topological connection relationship includes the power transmission position relationship among the transformer station, distribution station, and load point. In the city power network, the power directed edges among the infrastructure nodes are established according to the power topological connection relationship, and the direction of the power directed edge represents the power transmission direction. The service relationships between the urban drainage network, the urban transportation network, and the urban power network are obtained, and cross-network directed dependency edges are constructed between the urban drainage network, the urban transportation network, and the urban power network according to the service relationships to obtain the infrastructure network. The direction of the cross-network directed dependency edges represents the service dependency direction in the service relationships.

[0021] Furthermore, based on the service relationships, cross-network directed dependency edges are constructed between the urban drainage network, the urban transportation network, and the urban power network to obtain the infrastructure network, including: The infrastructure nodes in the urban drainage network, the urban transportation network, and the urban power network are combined to obtain node pairs; wherein, the infrastructure nodes in the urban drainage network, the urban transportation network, and the urban power network are combined to obtain node pairs. ; Calculate the spatial Euclidean distance between the infrastructure nodes in the node pair; If the spatial Euclidean distance is less than or equal to the dependency radius threshold, then it is determined that the infrastructure node in the node pair corresponding to the spatial Euclidean distance has the service relationship; Based on the service dependency direction, different infrastructure nodes with the service relationship are connected to obtain the cross-network directed dependency edge. The cross-network directed dependency edge, the urban drainage network, the urban transportation network, and the urban power network are then combined to obtain the infrastructure network; wherein, if the spatial Euclidean distance... ( D (This depends on the radius threshold, which can be set according to the actual situation), then a connection is established from the service provider node. v Pointing to the service dependency node u From the directed edges, we obtain the directed dependency edges across the network.

[0022] Step S20: Construct a mutual dependency matrix based on the infrastructure network, and determine the dependency weights based on the mutual dependency matrix; Among them, dependency weight is used to represent the strength of the dependency relationship between different infrastructure nodes.

[0023] Optionally, constructing a mutual dependency matrix based on the infrastructure network includes: Obtain the pipeline drainage capacity and service area between the infrastructure nodes corresponding to the directed drainage edges, and construct the drainage weights of the directed drainage edges based on the pipeline drainage capacity and the service area; wherein, a drainage weight is assigned to each directed drainage edge. , This is a weighting function used to calculate the drainage capacity of the pipeline. and service area Normalization and weighted fusion are performed to convert them into dimensionless, standardized dependent weights representing connection strength, function Linear weighting, piecewise function or empirical fitting can be used to reflect the comprehensive influence of different types of parameters on dependence strength; Obtain the traffic flow between the infrastructure nodes corresponding to the traffic directed edge, and construct the traffic weight of the traffic directed edge according to the traffic flow; wherein each traffic directed edge is assigned a traffic weight , through a weight calculation function, for mapping road traffic capacity or traffic flow parameters to a predefined weight interval to quantify the influence of traffic flow strength on inter-node dependence; Obtain the line power supply load capacity and upstream and downstream power supply dependence ratio between the infrastructure nodes corresponding to the power directed edge, and construct the power supply weight of the power directed edge according to the line power supply load capacity and the upstream and downstream power supply dependence ratio; wherein each power directed edge is assigned a power supply weight , wherein the weight calculation function is used to weight correct the line power supply load capacity according to the upstream and downstream power supply proportion dependence parameter to calculate the power supply dependence strength between nodes; According to the spatial Euclidean distance, the dependence weight of the cross-network directed dependence edge is constructed, and the mutual dependence matrix is constructed according to the dependence weight, the drainage weight, the traffic weight and the power supply weight; wherein each cross-network directed dependence edge is assigned a dependence weight The weight is calculated according to the distance attenuation principle, that is , wherein the function is a monotonically decreasing function satisfying (maximum dependence when distance is 0) and (no dependence when distance reaches threshold D ).

[0024] The constructed node set and internal connection edge (including weight ) of the drainage, traffic and power three sub-networks and the overall network of cross-system dependence edge (including weight ) are integrated into a unified mutual dependence matrix A ; wherein, represents the node connection matrix inside the drainage network, and the element value is the drainage dependence weight between nodes ; a node connection matrix representing the connection between nodes within the traffic network, with element values being the traffic dependency weight between nodes ; a node connection matrix representing the connection between nodes within the power network, with element values being the power supply dependency weight between nodes ; a dependency relationship between the drainage network and the traffic network, reflecting the strength of the drainage facility operation being constrained by traffic passing or road drainage capacity; a dependency relationship between the drainage network and the power network, reflecting the dependency strength of drainage pumping stations and other facilities on the power supply network; a dependency relationship between the traffic network and the power network, reflecting the dependency degree of traffic signals, lighting and other equipment on power supply; accordingly, a dependency relationship between the traffic network and the drainage network, reflecting the degree of road traffic being affected by drainage capacity; a dependency relationship between the power network and the drainage network, reflecting the influence of power supply facilities being affected by the safe operation conditions of the drainage system; a dependency relationship between the power network and the traffic network, reflecting the strength of the power supply network operation and maintenance being constrained by road traffic conditions; Step S30, obtaining city meteorological observation data, and determining an initial impact node in the infrastructure network according to the city meteorological observation data; Wherein, the artificial setting instruction for the city meteorological observation data is obtained to determine the initial impact facility, and the infrastructure node corresponding to the initial impact facility in the infrastructure network is set as the initial impact node.

[0025] In this step, based on the city meteorological observation data (such as extreme rainfall intensity, storm duration, spatial distribution, etc.), the initial impact node set (such as low-lying area, bottleneck drainage node, etc.) is determined.

[0026] Step S40, obtaining the upstream and downstream relationship of nodes in the infrastructure network, and inputting the infrastructure network, the upstream and downstream relationship of nodes, the dependency weight and the initial impact node into a cascade propagation simulation model for propagation simulation to obtain a city rainstorm impact cascade propagation simulation result; Wherein, based on the modeling framework of the geographical cascade model (Geo-PN Model), the cascade propagation simulation model is constructed, the step-by-step influence process of the initial impact node on the downstream nodes is simulated, and the node state and propagation path are dynamically evolved to depict the impact diffusion characteristics under extreme events. The core state of the cascade propagation simulation model is a five-tuple: ; representing the probability of each node being impacted at the current time; representing the strength of the mutual dependency relationship between nodes; denotes a set of upstream nodes (parent nodes); denotes a set of downstream nodes (child nodes); denotes a current state of the node, denotes failure, denotes normal.

[0027] The cascade propagation simulation model adopts an iterative updating mechanism. For all nodes that have not failed at the current time j , the impact intensity is calculated by the cumulative transmission of the failed node set .

[0028] Optionally, the infrastructure network, the upstream and downstream relationships of the nodes, the dependency weight, and the initial impact node are input into the cascade propagation simulation model for propagation simulation to obtain a cascade propagation simulation result of urban rainstorm impact, including: In the cascade propagation simulation model, the upstream and downstream nodes of the infrastructure nodes are determined according to the upstream and downstream relationships of the nodes, and the initial impact node is set as a failed node; The impact intensity of the failed node on the corresponding downstream node is calculated according to the dependency weight, and an impact probability is calculated according to the impact intensity; If the impact probability of any infrastructure node is greater than a probability threshold, the infrastructure node is determined as the failed node; wherein the impact probability of the infrastructure node at the current time step is compared with the probability threshold to determine the node state: The step of calculating the impact intensity of the failed node on the corresponding downstream node according to the dependency weight is returned to be executed until the cascade propagation simulation model meets a simulation termination condition, and the propagation path and the node state change of the failed node at each time step are output to obtain the cascade propagation simulation result of urban rainstorm impact.

[0029] Further, the formula for calculating the impact intensity of the failed node on the corresponding downstream node according to the dependency weight includes: wherein, denotes the failed node i impacting on its downstream nodes j at the current time step, denotes the dependency weight between the failed node i and its downstream nodes j , denotes a set of normal nodes in a normal state at the current time step, denote the failed nodes i and their downstream nodes k , and the dependency weights between them, denote the failed node set.

[0030] Further, the formula used to calculate the impact probability according to the impact intensity includes: wherein, denote the impact probability of the downstream node j in the current time step, denote the impact probability of the downstream node j in the last time step, denote the nodes in the failed node set.

[0031] Preferably, in each propagation time step t , for the node j that is not failed at the current time, the propagation path of a previous failed node , if the propagation is successful (the node j is determined as a failed node), it is considered that the path has completed the propagation, and the propagation path is blocked, and the subsequent propagation is no longer repeated and superimposed; if the propagation fails (the impact probability of the infrastructure node is less than or equal to the probability threshold), the potential risk value is calculated: wherein, is the current propagation probability of the upstream node i , and is introduced to update the posterior propagation probability to represent the influence caused by the path that fails in the propagation but has potential threat. It is used to record the risk path that is temporarily “omitted” due to the single-step propagation failure, and provides support for the impact accumulation and state judgment in the subsequent time steps. For the node j that fails in the propagation but has potential risk, the propagation probability thereof is updated in the next step as: denote the propagation probability in the next time step.

[0032] In the embodiment, the simulation process is iterated in units of fixed time intervals, and each iteration is regarded as one “step”. Each step corresponds to an actual time, for example, one step represents two hours. In each propagation, the state of each node is updated according to the propagation rule, and the propagation path, node impact intensity and risk information are recorded to obtain the simulation result of the urban rainstorm impact cascade propagation.

[0033] The simulation process continues until any of the following stopping conditions is met State stabilization: If the state of all nodes in the current time step is exactly the same as the previous time step, and there is no new node change, it indicates that the state has reached stability, the cascade propagation simulation model meets the simulation termination condition, and the propagation stops. Iteration step reaches the upper limit: When the number of propagation reaches the preset maximum value, the cascade propagation simulation model meets the simulation termination condition, and the iteration is automatically terminated to prevent invalid calculation. Failure threshold exceeds: If at a certain time point, the cumulative failure node ratio in the cascade propagation simulation model exceeds the pre-set tolerable range (such as 70%), the cascade propagation simulation model is considered to be unstable as a whole, and the simulation is immediately terminated, that is: wherein, represents the number of failed nodes in the t step, is the total number of nodes, is the tolerance threshold. After the simulation is stopped, the analysis indicators such as the propagation path of each time step, the affected node list, and the functional failure rate curve are output for subsequent visualization and decision support.

[0034] After the cascade propagation simulation is completed, the propagation path, node state change and functional decay process of each time step are comprehensively analyzed, and various types of visualizations such as propagation Sankey diagram and heat map are generated based on the simulation results, which are convenient for intuitive understanding of the impact propagation process and identification of key influencing links. For example, the Sankey diagram can show the diffusion path and propagation intensity of the impact in multiple infrastructure networks, which helps to identify the main propagation chain and key relay nodes; the heat map depicts the spatial distribution pattern and influence intensity change of the affected area, highlighting the vulnerable areas and high-frequency areas in the system.

[0035] The embodiment can accurately simulate the cascade effect of rain and flood disasters along the infrastructure network. The city multi-layer interdependent network is constructed by using a weighted directed graph, which can accurately integrate and depict the asymmetric interdependent relationship between urban infrastructure such as roads, drainage and power at a fine scale. By defining the threshold discrimination function of cascade propagation, the cascade effect and indirect impact of rain and flood impact along the city infrastructure network under various scenarios can be simulated, effectively revealing the cascade response characteristics of the city complex system.

[0036] The embodiment can realize the whole-chain propagation path tracking and key risk identification of rain flood disaster impact, and through the combination of the dynamic cascade simulation method, the whole-chain path tracking and key risk identification of the city rain flood disaster impact along the infrastructure network can be realized, specifically including the high-risk area (propagation key node) vulnerable to impact, the relay node (propagation important hub) accelerating the diffusion of network function failure, and the terminal node (propagation termination node) capable of blocking propagation, thereby providing support for the timely identification, priority protection and intervention strategy of key risks.

[0037] The embodiment can support the loss quantification and comprehensive evaluation of the cascade influence of city rain flood disaster, break through the limitation of the prior art in quantifying the indirect influence of city rain flood disaster, that is, it is difficult to track the dynamic propagation path and quantify the function attenuation, and can record the persistence change of node state on the basis of simulating the propagation process of cascade effect, and accurately quantify the failure degree of city overall function based on the key city infrastructure function evaluation index, thereby providing objective and reliable technical and method support for disaster loss evaluation and resource allocation.

[0038] The embodiment has good adaptability and scenario expansion capability, has multi-scenario configuration and analysis capability, can efficiently perform multi-scheme simulation through setting different intensity, spatial distribution and duration of rainfall impact scenarios, and various propagation rules and threshold parameter combinations, and can intuitively compare and analyze the simulation results (such as propagation range, key node failure condition, system function risk evaluation) under different scenarios, so as to facilitate the identification of the response characteristics of the system under different impact scenarios, and has good expansion potential.

[0039] In the embodiment, the city key infrastructure information is acquired to effectively construct the infrastructure network, the interdependence matrix is effectively constructed based on the infrastructure network, the strength of the dependence relationship between different infrastructure nodes is effectively determined based on the interdependence matrix, the city meteorological observation data is acquired to effectively determine the initial impact node, the infrastructure network, the upstream and downstream relationship of the node, the dependence weight and the initial impact node are input into the cascade propagation simulation model for propagation simulation to effectively realize the cascade simulation of the city rain flood impact from the local node triggering to the range diffusion process, thereby improving the accuracy of the city rain flood disaster impact propagation simulation.

[0040] Embodiment two Please refer to Figure 2 is a structural schematic diagram of a city rain flood impact cascade propagation simulation system 100 provided by the second embodiment of the present application, which comprises: The network construction module 10 is used for acquiring city key infrastructure information, and constructing an infrastructure network according to the city key infrastructure information.

[0041] Optionally, the network construction module 10 is further configured to: acquire a city drainage pipe network and a drainage topology connection relationship in the city critical infrastructure information, and set a pump station, a manhole and a water outlet in the city drainage pipe network as the infrastructure nodes; In the city drainage pipe network, drainage directed edges between the infrastructure nodes are established according to the drainage topology connection relationship, and a direction of the drainage directed edge represents a rainwater flow direction; acquire a city traffic network and a traffic topology connection relationship in the city critical infrastructure information, and set a road intersection and a traffic hub in the city traffic network as the infrastructure nodes; In the city traffic network, traffic directed edges between the infrastructure nodes are established according to the traffic topology connection relationship, and a direction of the traffic directed edge represents a traffic passing direction; acquire a city power network and a power topology connection relationship in the city critical infrastructure information, and set a transformer substation, a distribution station and a load point in the city power network as the infrastructure nodes; In the city power network, power directed edges between the infrastructure nodes are established according to the power topology connection relationship, and a direction of the power directed edge represents a power transmission direction; acquire a service relationship between the city drainage pipe network, the city traffic network and the city power network, and construct cross-network directed dependency edges between the city drainage pipe network, the city traffic network and the city power network according to the service relationship to obtain the infrastructure network, and a direction of the cross-network directed dependency edge represents a service dependency direction in the service relationship.

[0042] Further, the network construction module 10 is further configured to: combine the infrastructure nodes in the city drainage pipe network, the city traffic network and the city power network to obtain node pairs; calculate a spatial Euclidean distance between the infrastructure nodes in the node pairs; if the spatial Euclidean distance is less than or equal to a dependency radius threshold, determine that the infrastructure nodes in the node pairs corresponding to the spatial Euclidean distance exist the service relationship; according to the service dependency direction, connect different infrastructure nodes existing the service relationship to obtain the cross-network directed dependency edges, and combine the cross-network directed dependency edges, the city drainage pipe network, the city traffic network and the city power network to obtain the infrastructure network.

[0043] The weight determination module 11 is configured to construct a mutual dependence matrix according to the infrastructure network, and determine dependence weights according to the mutual dependence matrix, wherein the dependence weights are used to represent the strength of dependence between different infrastructure nodes in the infrastructure network.

[0044] Optionally, the weight determination module 11 is further configured to: acquire pipe drainage capacity and service area corresponding to the drainage directed edges between the infrastructure nodes, and construct drainage weights of the drainage directed edges according to the pipe drainage capacity and the service area; acquire traffic flow corresponding to the traffic directed edges between the infrastructure nodes, and construct traffic weights of the traffic directed edges according to the traffic flow; acquire line power supply load capacity and upstream and downstream power supply dependence proportion corresponding to the power directed edges between the infrastructure nodes, and construct power supply weights of the power directed edges according to the line power supply load capacity and the upstream and downstream power supply dependence proportion; construct dependence weights of the cross-network directed dependence edges according to the spatial Euclidean distance, and construct the mutual dependence matrix according to the dependence weights, the drainage weights, the traffic weights and the power supply weights.

[0045] The initial impact module 12 is configured to acquire urban meteorological observation data, and determine initial impact nodes in the infrastructure network according to the urban meteorological observation data.

[0046] The impact simulation module 13 is configured to acquire upstream and downstream relationships of nodes in the infrastructure network, and input the infrastructure network, the upstream and downstream relationships of the nodes, the dependence weights and the initial impact nodes into a cascade propagation simulation model to perform propagation simulation, so as to obtain a city rainstorm impact cascade propagation simulation result.

[0047] Optionally, the impact simulation module 13 is further configured to: in the cascade propagation simulation model, determine upstream nodes and downstream nodes of the infrastructure nodes according to the upstream and downstream relationships of the nodes, and set the initial impact nodes as failure nodes; calculate impact strength of the failure nodes on corresponding downstream nodes according to the dependence weights, and calculate impact probabilities according to the impact strength; if the impact probability of any infrastructure node is greater than a probability threshold, determine the infrastructure node as the failure node; return to perform the step of calculating the impact strength of the failure nodes on corresponding downstream nodes according to the dependence weights, until the cascade propagation simulation model meets a simulation termination condition, output propagation paths and node state changes of the failure nodes in each time step, so as to obtain the city rainstorm impact cascade propagation simulation result.

[0048] Further, the formula for calculating the impact intensity of the failed node on the corresponding downstream node according to the dependency weight comprises: wherein, represents the failed node i at the current time step, j the intensity of the impact on its downstream nodes, represents the failed node i and its downstream nodes, j the dependency weight between, represents the set of normal nodes in normal state at the current time step, represents the failed node i and its downstream nodes, k the dependency weight between, represents the set of failed nodes.

[0049] Further, the formula for calculating the impact probability according to the impact intensity comprises: wherein, represents the impact probability of the downstream node j at the current time step, represents the impact probability of the downstream node j at the last time step, represents the node in the set of failed nodes.

[0050] In the embodiment, the city critical infrastructure information is acquired to effectively construct the infrastructure network, the infrastructure network is used to effectively construct the interdependence matrix, the interdependence matrix is used to effectively determine the dependency strength between different infrastructure nodes, the city meteorological observation data is acquired to effectively determine the initial impact node, the infrastructure network, the upstream and downstream relationship of the node, the dependency weight and the initial impact node are input into the cascade propagation simulation model to effectively realize the cascade simulation of the process of the city rainstorm impact from the local node triggering to the range diffusion, and the accuracy of the city rainstorm disaster impact propagation simulation is improved.

[0051] Embodiment Three Figure 3 is a structural block diagram of a terminal device 2 provided by the third embodiment of the present application. As shown in Figure 3As shown, the terminal device 2 of the embodiment comprises a processor 20, a memory 21, and a computer program 22 stored in the memory 21 and executable on the processor 20, for example, a program of the urban rainstorm impact cascade propagation simulation method. The processor 20 implements the steps in each of the above embodiments of the urban rainstorm impact cascade propagation simulation method when executing the computer program 22.

[0052] For example, the computer program 22 can be divided into one or more modules stored in the memory 21 and executed by the processor 20 to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program 22 in the terminal device 2. The terminal device can include, but is not limited to, the processor 20 and the memory 21.

[0053] The processor 20 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0054] The memory 21 can be an internal storage unit of the terminal device 2, for example, a hard disk or a memory of the terminal device 2. The memory 21 can also be an external storage device of the terminal device 2, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 21 can include both the internal storage unit and the external storage device of the terminal device 2. The memory 21 is used to store the computer program and other programs and data required by the terminal device. The memory 21 can also be used to temporarily store data that has been output or will be output.

[0055] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0056] If the integrated module is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. The computer readable storage medium can be non-volatile or volatile. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable storage medium can include any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content included in the computer readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable storage medium does not include electrical carrier signals and telecommunication signals.

[0057] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for simulating the cascade propagation of urban stormwater flood impacts, characterized in that, The method comprises: obtaining city critical infrastructure information, and constructing an infrastructure network according to the city critical infrastructure information; constructing a mutual dependence matrix according to the infrastructure network, and determining a dependence weight according to the mutual dependence matrix, the dependence weight being used to represent the strength of the dependence relationship between different infrastructure nodes in the infrastructure network; obtaining city meteorological observation data, and determining an initial impact node in the infrastructure network according to the city meteorological observation data; obtaining upstream and downstream relationships of nodes in the infrastructure network, and inputting the infrastructure network, the upstream and downstream relationships of the nodes, the dependence weight and the initial impact node into a cascade propagation simulation model to perform propagation simulation, to obtain a city rainstorm impact cascade propagation simulation result.

2. The urban stormwater flood impact cascade propagation simulation method of claim 1, wherein, The method of inputting the infrastructure network, the upstream and downstream relationships of the nodes, the dependence weight and the initial impact node into a cascade propagation simulation model to perform propagation simulation, to obtain a city rainstorm impact cascade propagation simulation result, comprises: in the cascade propagation simulation model, determining upstream nodes and downstream nodes of the infrastructure nodes according to the upstream and downstream relationships of the nodes, and setting the initial impact node as a failed node; calculating an impact strength of the failed node on corresponding downstream nodes according to the dependence weight, and calculating an impact probability according to the impact strength; if the impact probability of any infrastructure node is greater than a probability threshold, determining the infrastructure node as the failed node; returning to performing the step of calculating the impact strength of the failed node on corresponding downstream nodes according to the dependence weight, until the cascade propagation simulation model meets a simulation termination condition, outputting the propagation path and node state change of the failed node in each time step, to obtain the city rainstorm impact cascade propagation simulation result.

3. The urban stormwater flood impact cascade propagation simulation method of claim 2, wherein, The formula used to calculate the impact strength of the failed node on corresponding downstream nodes according to the dependence weight comprises: wherein, denotes the failed node i at the current time step j the intensity of the impact, denotes the failed node i and its downstream nodes j the dependency weight between them, denotes the set of normal nodes at the current time step, denotes the failed node i and its downstream nodes k the dependency weight between them, denotes the set of failed nodes.

4. The urban stormwater flood impact cascade propagation simulation method of claim 3, wherein, The formula used to calculate the impact probability according to the impact strength comprises: wherein, denotes the impact probability of a downstream node j in the current time step, denotes the impact probability of a downstream node j in the previous time step, denotes a node in the set of failed nodes.

5. The urban stormwater flood impact cascade propagation simulation method of claim 1, wherein, constructing an infrastructure network according to the city critical infrastructure information, comprises: obtaining a city drainage pipe network and a drainage topology connection relationship in the city critical infrastructure information, and setting a pump station, a manhole and a water outlet in the city drainage pipe network as the infrastructure nodes; in the city drainage pipe network, establishing drainage directed edges between the infrastructure nodes according to the drainage topology connection relationship, the direction of the drainage directed edges representing the rainwater flow direction; obtaining a city traffic network and a traffic topology connection relationship in the city critical infrastructure information, and setting a road intersection and a traffic hub in the city traffic network as the infrastructure nodes; in the city traffic network, establishing traffic directed edges between the infrastructure nodes according to the traffic topology connection relationship, the direction of the traffic directed edges representing the traffic passing direction; obtaining a city power network and a power topology connection relationship in the city critical infrastructure information, and setting a transformer substation, a distribution station and a load point in the city power network as the infrastructure nodes; In the urban power network, power directed edges between the infrastructure nodes are established according to the power topology connection relationship, and the direction of the power directed edge represents the power transmission direction; Obtaining service relationships between the urban drainage pipe network, the urban traffic network and the urban power network, and constructing cross-network directed dependency edges between the urban drainage pipe network, the urban traffic network and the urban power network according to the service relationships to obtain the infrastructure network, wherein the direction of the cross-network directed dependency edge represents the service dependency direction in the service relationship.

6. The urban stormwater flood impact cascade propagation simulation method of claim 5, wherein, Constructing cross-network directed dependency edges between the urban drainage pipe network, the urban traffic network and the urban power network according to the service relationships to obtain the infrastructure network, comprising: Combining the infrastructure nodes in the urban drainage pipe network, the urban traffic network and the urban power network to obtain node pairs; Calculating spatial Euclidean distances between the infrastructure nodes in the node pairs; If the spatial Euclidean distance is less than or equal to a dependency radius threshold, it is determined that the infrastructure nodes in the node pair corresponding to the spatial Euclidean distance exist the service relationship; According to the service dependency direction, connecting different infrastructure nodes existing the service relationship to obtain the cross-network directed dependency edge, and combining the cross-network directed dependency edge, the urban drainage pipe network, the urban traffic network and the urban power network to obtain the infrastructure network.

7. The urban stormwater flood impact cascade propagation simulation method of claim 6, wherein, Constructing a mutual dependency matrix according to the infrastructure network, comprising: Obtaining pipe drainage capacity and service areas between the infrastructure nodes corresponding to the drainage directed edge, and constructing drainage weights of the drainage directed edge according to the pipe drainage capacity and the service areas; Obtaining traffic flow between the infrastructure nodes corresponding to the traffic directed edge, and constructing traffic weights of the traffic directed edge according to the traffic flow; Obtaining line power supply load capacity and upstream and downstream power supply dependency proportions between the infrastructure nodes corresponding to the power directed edge, and constructing power supply weights of the power directed edge according to the line power supply load capacity and the upstream and downstream power supply dependency proportions; Constructing dependency weights of the cross-network directed dependency edge according to the spatial Euclidean distances, and constructing the mutual dependency matrix according to the dependency weights, the drainage weights, the traffic weights and the power supply weights.

8. An urban stormwater flood impact cascade propagation simulation system, characterized in that, The system comprises: A network construction module configured to obtain urban critical infrastructure information and construct an infrastructure network according to the urban critical infrastructure information; A weight determination module configured to construct a mutual dependency matrix according to the infrastructure network, and determine dependency weights according to the mutual dependency matrix, wherein the dependency weights are used to represent the strength of dependency relationships between different infrastructure nodes in the infrastructure network; An initial impact module configured to obtain urban meteorological observation data and determine initial impact nodes in the infrastructure network according to the urban meteorological observation data; An impact simulation module is configured to acquire upstream and downstream relationships of nodes in the infrastructure network, and perform a propagation simulation on the infrastructure network, the upstream and downstream relationships of the nodes, the dependency weights, and the initial impact node input cascade propagation simulation model to obtain a cascade propagation simulation result of urban rainstorm flood impact.

9. The urban stormwater flood impact cascade propagation simulation system of claim 8, wherein, The impact simulation module is further configured to: In the cascade propagation simulation model, determine upstream and downstream nodes of the infrastructure nodes according to the upstream and downstream relationships of the nodes, and set the initial impact node as a failed node; calculate an impact intensity of the failed node on a corresponding downstream node according to the dependency weights, and calculate an impact probability according to the impact intensity; if the impact probability of any infrastructure node is greater than a probability threshold, determine the infrastructure node as the failed node; return to perform the step of calculating the impact intensity of the failed node on the corresponding downstream node according to the dependency weights until the cascade propagation simulation model meets a simulation termination condition, and output a propagation path and a node state change of the failed node in each time step to obtain the cascade propagation simulation result of urban rainstorm flood impact.

10. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: The computer program, when executed by a processor, implements the steps of the method for simulating cascade propagation of urban rainstorm flood impact according to any one of claims 1 to 7.

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