Disaster chain-based coupling method, device and product for urban system simulation model

Abstract

The application discloses a kind of urban system simulation model coupling method, equipment and product based on disaster chain, which comprises the following steps: collecting city related data, water disaster related data;City related data is classified according to different city system types, and the first modeling data of different types of city system is obtained;Water disaster related data is classified, and the second modeling data related to water disaster affecting the operation of different types of city system is obtained;According to the first modeling data and / or second modeling data of different types of city system, different types of city system model are constructed;Disaster chain analysis is carried out on water disaster related data, and the disaster chain of each type of water disaster is determined;Coupling is carried out on city system model and the disaster chain of each type of water disaster, and the city system disaster simulation model of the disaster chain of fusion composite water disaster is generated;The application considers the disaster chain of composite water disaster to carry out city system simulation model coupling, which can improve the accuracy of composite water disaster prediction faced by city.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, device and product for coupling urban system simulation models based on disaster chains. Background Technology

[0002] Currently, disaster simulation modeling research mainly focuses on assessing the impact of single disasters on single urban systems (such as transportation systems and land use systems), while the field of disaster risk assessment is only beginning to gradually involve comprehensive analysis of the entire urban system. Existing disaster simulation schemes, on the one hand, primarily focus on extreme water disaster simulations for water-related disasters, and the types of complex water disasters simulated are relatively few, with the impact on urban systems limited to the effects of surface water accumulation; on the other hand, simulations of complex disasters mainly focus on various disasters such as floods, droughts, landslides, debris flows, avalanches, and astronomical tides-storm surges-floods-saltwater intrusion-precipitation, but these simulations are conducted in coastal areas, river networks, and offshore areas, without involving cities.

[0003] In summary, while the field of disaster simulation has made some attempts to explore the interactions and impacts of complex or multi-hazard events, significant gaps remain in research on how complex flood disasters affect urban systems as a whole. Existing simulation methods do not consider the complex effects and chain reactions of complex flood disasters on urban systems as a whole, thus affecting the real-time performance and accuracy of urban flood predictions and resulting in low prediction accuracy. Summary of the Invention

[0004] To address the problems existing in the prior art, embodiments of the present invention provide a method, device, and product for coupling urban system simulation models based on disaster chains. By considering the disaster chains of complex floods in coupling urban system simulation models, the accuracy of predicting complex flood hazards facing cities can be improved.

[0005] In a first aspect, embodiments of the present invention provide a method for coupling a city system simulation model based on a disaster chain, comprising:

[0006] Collect city-related data and water disaster-related data;

[0007] The city-related data are classified according to different city system types to obtain the first modeling data for different types of city systems;

[0008] The water disaster-related data are classified to obtain second modeling data related to water disasters that affect the operation of different types of urban systems;

[0009] Based on the first modeling data and / or the second modeling data of different types of urban systems, construct different types of urban system models;

[0010] Disaster chain analysis was performed on the aforementioned water disaster-related data to determine the disaster chains for each type of water disaster;

[0011] The urban system model and the disaster chains of various types of water disasters are coupled to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters.

[0012] As an improvement to the above scheme, the city-related data includes: urban topography data, river network data, transportation network data, infrastructure data, land use data, soil data, building data, energy system data, geographic data, socio-economic data, population data, travel behavior data, water source data, water demand data, pipeline operation control data, and overflow water volume data; the water disaster-related data includes: rainstorm disaster data, river flood data, ocean water level change data, and meteorological data.

[0013] As an improvement to the above scheme, the urban system model includes: urban waterways and stormwater pipe systems; the first modeling data of the urban waterways and stormwater pipe systems includes: urban topography data, waterway network data, land use data, and overflow water volume data; the second modeling data of the urban waterways and stormwater pipe systems includes: rainstorm disaster data, river flood data, and ocean water level change data.

[0014] The method includes the following construction process for urban waterways and stormwater drainage systems:

[0015] Initialize the parameters of the rainstorm and flood management model;

[0016] The urban topography data, river network data, land use data, overflow water data, rainstorm disaster data, river flood data, and ocean water level change data are input into the initialized rainstorm flood management model for simulation, and the model simulation results are output.

[0017] Based on the model simulation results and the pre-collected observation data of urban rivers and stormwater pipes, the parameters of the stormwater and flood management model are adjusted until the model simulation results output by the stormwater and flood management model and the loss of the observation data are within the preset loss threshold range, thereby obtaining the urban river and stormwater pipe system.

[0018] As an improvement to the above scheme, the urban system model includes: an urban surface water simulation system; the first modeling data of the urban surface water simulation system includes: urban topography data, land use data, and soil data; the second modeling data of the urban surface water simulation system includes: rainstorm disaster data; the urban surface water simulation system is modeled using a distributed hydrological model based on the urban topography data, the river network data, the land use data, the soil data, and the rainstorm disaster data.

[0019] The urban system model includes: an urban energy system; the first modeling data of the urban energy system includes: building data, geographic data, energy system data, and socioeconomic data; the second modeling data of the urban energy system includes: meteorological data; the urban energy system is modeled using an urban energy modeling model based on the building data, geographic data, energy system data, socioeconomic data, and meteorological data.

[0020] The urban system model includes: an urban transportation network system; the first modeling data of the urban transportation network system includes: population data, transportation network data, infrastructure data, and travel behavior data; the urban transportation network system is modeled using a multi-agent-based traffic simulation model based on the population data, the transportation network data, the infrastructure data, and the travel behavior data.

[0021] The urban system model includes: an urban water supply system; the first modeling data of the urban water supply system includes: river network data, water source data, water demand data, and network operation control data; the urban water supply system is modeled using a water supply network hydraulic and water quality simulation model based on the river network data, the water source data, the water demand data, and the network operation control data.

[0022] As an improvement to the above scheme, the coupling of the urban system model and the disaster chains of various types of water disasters to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters includes:

[0023] Establish a connection between the urban river and stormwater pipe system and the urban surface water simulation system to generate urban water circulation paths;

[0024] Establish a connection between the urban surface water simulation system and the urban energy system to generate an urban energy control path;

[0025] Establish a connection between the urban energy system and the urban transportation network system to generate a first urban traffic travel control path;

[0026] Establish a connection between the urban energy system and the urban water supply system to generate a first urban water supply control path;

[0027] Establish a connection between the urban surface water simulation system and the urban transportation network system to generate a second urban traffic travel control path;

[0028] Establish a connection between the urban surface water simulation system and the urban water supply system to generate a second urban water supply control path; establish a connection between secondary disasters in the disaster chain of various types of water disasters and various systems in the urban system model to generate urban secondary disaster impact paths;

[0029] Based on the urban system model, the urban water circulation path, the urban energy control path, the first urban traffic control path, the first urban water supply control path, the second urban traffic control path, the second urban water supply control path, and the urban secondary disaster impact path, the urban system disaster simulation model is generated.

[0030] As an improvement to the above scheme, the step of establishing the connection between the urban river and stormwater pipeline system and the urban surface water simulation system to generate urban water circulation paths includes:

[0031] Establish a connection between the water overflow node of the urban river and stormwater pipe system and the surface flow node of the urban surface water simulation system;

[0032] Establish connections between the surface water collection nodes of the urban surface water simulation system and the network nodes of the urban river and stormwater pipeline system.

[0033] In the operation of the urban river and stormwater pipeline system and the urban surface water simulation system, the urban water circulation path is formed through the water overflow node, the surface flow node, the surface water convergence node, and the pipeline node.

[0034] As an improvement to the above scheme, the step of establishing a connection between the urban surface water simulation system and the urban energy system to generate an urban energy control path includes:

[0035] Establish a connection between the regional water depth detection node of the urban surface water simulation system and the power supply equipment control node of the urban energy system;

[0036] In the operation of the urban surface water simulation system and the urban energy system, a one-way urban energy control path is formed through the regional water depth detection node and the power supply equipment control node.

[0037] As an improvement to the above solution, the method further includes:

[0038] Acquire data for predicting water disasters; wherein the data for predicting water disasters includes at least one of the following: data for predicting rainstorm disasters, data for predicting river floods, data for predicting ocean level changes, and data for predicting meteorological conditions.

[0039] The predicted water disaster data is input into the urban system disaster simulation model for simulation to obtain urban response strategies under the predicted water disaster data.

[0040] In a second aspect, embodiments of the present invention provide a disaster chain-based urban system simulation model coupling device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the disaster chain-based urban system simulation model coupling method as described in any one of the first aspects.

[0041] Thirdly, embodiments of the present invention provide a computer program product, including a computer program / instruction, which, when executed by a processor, implements the urban system simulation model coupling method based on disaster chains as described in any one of the first aspects.

[0042] Compared to existing technologies, this invention provides a method, device, and product for coupling urban system simulation models based on disaster chains. This involves collecting urban-related data and water disaster-related data; classifying the urban-related data according to different urban system types to obtain first modeling data for different types of urban systems; classifying the water disaster-related data to obtain second modeling data related to water disasters affecting the operation of different types of urban systems; constructing different types of urban system models based on the first and / or second modeling data for different types of urban systems; performing disaster chain analysis on the water disaster-related data to determine the disaster chains for each type of water disaster; and coupling the urban system models and the disaster chains for each type of water disaster to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters. This invention, by considering the disaster chains of complex water disasters in coupling urban system simulation models, can improve the accuracy of predicting complex water hazards facing cities. Attached Figure Description

[0043] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1This is a flowchart of a method for coupling a city system simulation model based on a disaster chain, provided in an embodiment of the present invention.

[0045] Figure 2 This is a schematic block diagram of the urban system simulation model provided in an embodiment of the present invention;

[0046] Figure 3 This is a structural block diagram of a city system simulation model coupling device based on a disaster chain, provided in an embodiment of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] It is understood that the various numerical designations used in the embodiments of this invention are merely for descriptive convenience and are not intended to limit the scope of this application. The order of the process numbers does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

[0049] In embodiments of the invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element. The term "a plurality or several" refers to two or more.

[0050] See Figure 1 , Figure 1 This is a flowchart illustrating a method for coupling a disaster chain-based urban system simulation model, as provided in an embodiment of the present invention. The method specifically includes:

[0051] S11: Collect city-related data and water disaster-related data;

[0052] S12: Classify the city-related data according to different city system types to obtain the first modeling data for different types of city systems;

[0053] S13: Classify the water disaster-related data to obtain second modeling data related to water disasters that affect the operation of different types of urban systems;

[0054] S14: Construct different types of urban system models based on the first modeling data and / or the second modeling data of different types of urban systems;

[0055] S15: Perform disaster chain analysis on the aforementioned water disaster-related data to determine the disaster chains for each type of water disaster;

[0056] S16: Couple the urban system model and the disaster chains of various types of water disasters to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters.

[0057] It should be noted that the urban system simulation model coupling method based on disaster chain described in the embodiments of the present invention can be executed by terminal devices such as servers and computers.

[0058] The city-related data includes, but is not limited to, the following:

[0059] Urban terrain data: This includes the surface elevation information (Digital Elevation Model, DEM) of the target city, usually saved in vector format .shp or raster format .tif.

[0060] River network data: This includes information such as the location, size, slope, elevation, and flow rate of objects such as rivers, rainwater pipes, manholes, outlets, water sources, user nodes, pumps, and valves within the target city, and is saved as a .inp file.

[0061] Traffic network data: including roads, intersections, public transportation routes, etc. within the target city, saved in .xml format.

[0062] Infrastructure data: This includes the location and capacity of activity locations (such as residential areas, commercial areas, schools, etc.) within the target city, saved in .xml or .shp format.

[0063] Land use data includes land cover types (such as vegetation, buildings, roads, etc.) within the target city, usually stored in raster format (such as .asc or .tif); it also includes parameters such as permeability and roughness of different land cover types within the target city, saved in tabular form .inp.

[0064] Soil data: including parameters such as soil type, permeability, and water holding capacity in the target city, stored in raster or tabular form.

[0065] Building data includes building geometry information (such as area, height, and shape), building type (such as residential and commercial), and building material properties (such as thermal conductivity) within the target city, saved in .csv or .shp format.

[0066] Energy system data: including the spatial distribution of the power system in the target city, configuration parameters (such as the efficiency and capacity of power equipment), and operating strategies, saved in Excel format.

[0067] Geographic data: including urban topography data, land use data, road network data (such as roads and intersections) within the target city, saved in .shp format.

[0068] Socioeconomic data: including information such as population density and energy prices in the target city, saved in .csv format.

[0069] Population data: This includes information such as the population of the target city, individual travel data, and activity plans, and is saved in .xml or .csv format.

[0070] Travel behavior data includes travel modes (such as walking, driving, public transportation) and travel time preferences of people in the target city, and is saved in .xml or .csv format.

[0071] Water source data: This includes information such as the location and supply capacity of water sources in the target city, and is saved in .inp format.

[0072] Water demand data: This includes data on the water consumption of each user node (including individuals, enterprises, etc.) within the target city over time, recorded in time series format and usually saved in .inp format.

[0073] Pipeline operation control data: including control rules for water pumps and valves in the target city's pipelines (such as opening, closing, and regulating water pumps and valves when set conditions are met), saved in .inp format.

[0074] Overflow water volume data: This includes overflow water volume data for pipelines or manholes in the target city, recorded in time series format, containing timestamps and spatial distribution, and stored in .asc or .csv format. It is generated by the SWMM-lisflood coupling module, which processes the water level and flow data output by SWMM.

[0075] The water disaster-related data includes, but is not limited to, the following data:

[0076] Rainstorm disaster data: This includes rainfall data recorded in time series for the target city. The rainfall data includes timestamps and the rainfall intensity corresponding to each timestamp (which can also be understood as the amount of rainfall at different times). The rainfall data is usually saved in .dat or .csv format.

[0077] River flood data: Includes upstream flow / water level data for the target city, saved in .inp format.

[0078] Ocean water level change data: including astronomical tide data, storm surge data, and sea level rise data for the target city, which can also be understood as downstream river flow / water level data, saved in .inp format.

[0079] Meteorological data: including time series data such as temperature, humidity, wind speed, and solar radiation of the target city, saved in .csv format.

[0080] As an optional implementation, the collected urban-related data and flood-related data of the target city can be preprocessed, including but not limited to: data cleaning, data imputation, and data transformation. Data cleaning removes invalid data from the urban-related and flood-related data; data imputation completes missing data; and data transformation extracts the required data features from the urban-related and flood-related data and converts them into a fixed data format, thus achieving data structuring. This data preprocessing effectively improves data quality and provides a reliable data foundation for subsequent urban system modeling.

[0081] This invention classifies collected urban-related data of a target city according to different urban system types (such as urban rivers and stormwater pipes, urban surface, urban energy, urban transportation networks, urban water supply, etc.) to obtain first modeling data related to different types of urban systems. It also obtains second modeling data related to water disasters, based on their impact on the operation of urban systems of the same type, to determine the impact on the operation of different types of urban systems. For example, data from the water disaster-related data that has a direct impact on a certain urban system is extracted as the second modeling data for that urban system; if the water disaster-related data has no direct impact on a certain urban system, then that urban system does not have second modeling data. After completing the above data classification, different types of urban system models are constructed based on the first and second modeling data (optional) for different types of urban systems. Then, disaster chain analysis is performed on the water disaster-related data to determine the disaster chains for each type of water disaster. Finally, the urban system model and the disaster chains for each type of water disaster are coupled to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters. This invention comprehensively considers the disaster chain of complex floods and couples it with an urban system simulation model. In the subsequent disaster prediction process, by inputting at least one predicted flood disaster data into the urban system disaster simulation model, the urban system disaster simulation model can simulate the direct or indirect impact of at least one predicted flood disaster data and its resulting disaster chain on various urban systems of the target city, thereby effectively improving the accuracy of predicting complex floods in cities.

[0082] Specifically, the urban system model includes: an urban river and stormwater drainage system, an urban surface water simulation system, an urban transportation network system, an urban water supply system, and an urban energy system. The urban river and stormwater drainage system includes an urban river network subsystem and a stormwater drainage subsystem.

[0083] Understandably, for urban river and stormwater drainage systems, urban topography data, river network data, and land use data directly determine the distribution of urban rivers and stormwater drainage systems, while rainstorm disaster data, river flood data, and ocean water level change data significantly affect the flow rate of rivers and stormwater drainage systems. For urban surface water simulation systems, urban topography data, land use data, and soil data directly determine the distribution of urban surfaces, while rainstorm disaster data significantly affects urban surface water flow. For urban transportation network systems, population data, transportation network data, infrastructure data, and travel behavior data directly determine the distribution of urban transportation networks. For urban water supply systems, river network data, water source data, water demand data, and pipeline operation control data directly determine the urban water supply situation. For urban energy systems, building data, geographic data, energy system data, and socioeconomic data directly determine the distribution of urban energy equipment, while meteorological data significantly affects the use of urban energy equipment.

[0084] Based on the above principles, the city-related data and water disaster-related data can be classified to construct first and / or second modeling data for different types of urban systems, as detailed below:

[0085] The first modeling data for the urban river and stormwater pipe system includes: urban topography data, river network data, land use data, and overflow water volume data; the second modeling data for the urban river and stormwater pipe system includes: rainstorm disaster data, river flood data, and ocean water level change data.

[0086] The first modeling data of the urban surface water simulation system includes: urban topography data, land use data, and soil data; the second modeling data of the urban surface water simulation system includes: rainstorm disaster data.

[0087] The first modeling data for the urban energy system includes: building data, geographic data, energy system data, and socioeconomic data; the second modeling data for the urban energy system includes: meteorological data.

[0088] The first modeling data for the urban transportation network system includes: population data, transportation network data, infrastructure data, and travel behavior data; the urban transportation network system has no second modeling data.

[0089] The first modeling data for the urban water supply system includes: river network data, water source data, water demand data, and network operation control data; the urban water supply system has no second modeling data.

[0090] Furthermore, the urban river and stormwater pipeline system is modeled using a stormwater and flood management model (such as a stormwater management model (SWMM)) based on urban topographic data, river network data, land use data, rainstorm disaster data, river flood data, and ocean water level change data; the urban surface water simulation system is modeled using a distributed hydrological model (such as a grid-based distributed hydrological model (Land InformationSystem-FLOOD routing model, LISFLOOD)) based on urban topographic data, river network data, land use data, soil data, and rainstorm disaster data; the urban energy system is modeled using an urban energy modeling model (such as a city energy analyst (CEA)) based on building data, geographic data, energy system data, socioeconomic data, and meteorological data; and the urban water supply system is modeled using the water supply network hydraulic and water quality simulation model EPANET based on river network data, water source data, water demand data, and pipeline operation control data. The urban transportation network system is modeled based on the population data, the transportation network data, the infrastructure data, and the travel behavior data using a multi-agent-based transportation simulation model (such as a multi-agent-based transportation simulation platform (MATSim)).

[0091] The construction process of each city system is explained in detail below:

[0092] (1) The construction process of urban waterways and stormwater drainage systems includes:

[0093] Initialize the parameters of the stormwater and flood management model (such as SWMM); for example, set the time step, simulation duration, and initial conditions of the stormwater and flood management model. Initial conditions include, but are not limited to, the initial water level / flow rate of the river and the initial flow rate of the stormwater pipes.

[0094] The urban topography data, river network data, land use data, rainstorm disaster data, river flood data, and ocean water level change data are input into the initialized rainstorm and flood management model SWMM for simulation, and the model simulation results are output.

[0095] Based on the simulation results of the model and the pre-collected observation data of urban rivers and stormwater pipes, the parameters of the stormwater and flood management model (SWMM) are adjusted until the model simulation results output by the SWMM and the loss of the observation data are within the preset loss threshold range, thereby obtaining the urban river and stormwater pipe system.

[0096] For example, the urban topography data, river network data, land use data, rainstorm disaster data, river flood data, and ocean water level change data obtained above are used as inputs to the initialized rainstorm flood management model SWMM, so that the rainstorm flood management model SWMM can run in simulation under the initial conditions, and perform parallel calculations of water level and flow rate according to the time step within the simulation time, and output the model simulation results; the model simulation results include time series data of water level and flow rate of river and pipeline.

[0097] Then, the simulation results of the above model are verified using observational data of urban rivers and stormwater pipes (including historical time series data of water level and flow in rivers and pipes within the same time period in the target city). For example, the loss between the historical time series data of water level and flow in rivers and pipes and the time series data of water level and flow in rivers and pipes in the model simulation results is calculated. If the loss between the two is within the preset loss threshold range, it means that the stormwater and flood management model SWMM has passed the verification and the construction of the urban river and stormwater pipe system has been completed; otherwise, the parameters of the stormwater and flood management model are readjusted and the simulation is run again until the stormwater and flood management model SWMM passes the verification.

[0098] (2) The construction process of the urban surface water simulation system includes:

[0099] Initialize the parameters of the distributed hydrological model (such as LISFLOOD); for example, set the time step, simulation duration, and initial conditions of the distributed hydrological model. The initial conditions at this time include, but are not limited to: initial soil moisture content, soil moisture distribution, initial water level / flow rate of the river channel, and initial flow rate of the stormwater pipes.

[0100] The urban topography data, the river network data, the land use data, the soil data, and the rainstorm disaster data are input into the initialized distributed hydrological model LISFLOOD for simulation and output the surface water flow simulation results.

[0101] Based on the surface water flow simulation results and the pre-collected urban surface water volume observation data, the parameters of the distributed hydrological model LISFLOOD are adjusted until the loss between the surface water flow simulation results output by the distributed hydrological model LISFLOOD and the water volume observation data is within a preset loss threshold range, thus obtaining the urban surface water simulation system.

[0102] Similarly, the urban topography data, river network data, land use data, soil data, and rainstorm disaster data obtained above are used as inputs to the initialized distributed hydrological model LISFLOOD. This allows the distributed hydrological model LISFLOOD to run under initial conditions and perform parallel calculations of surface inundation data according to time steps within the simulation duration, outputting surface water flow simulation results. These surface water flow simulation results include time series data of surface inundation.

[0103] Then, the simulation results of the above model are verified using water volume observation data (including historical time series data of surface inundation) from the same time period in the target city. For example, the loss between the water volume observation data and the time series data of water level and flow in the river and pipeline in the model simulation results is calculated. If the loss between the two is within the preset loss threshold range, it means that the distributed hydrological model LISFLOOD has passed the verification and the construction of the urban surface water simulation system has been completed; otherwise, the parameters of the storm flood management model are readjusted and the simulation is run again until the distributed hydrological model LISFLOOD passes the verification.

[0104] (3) The process of building an urban energy system includes:

[0105] Initialize the parameters of the urban energy modeling model (such as CEA); for example, set the simulation time range and energy system configuration of the urban energy modeling model. The initial conditions at this time include, but are not limited to: initial soil moisture content, soil moisture distribution, initial water level / flow rate of the river, and initial flow rate of the rainwater pipes.

[0106] The building data, geographic data, energy system data, socioeconomic data, and meteorological data are input into the initialized urban energy modeling model CEA for simulation, and the simulation results of the spatiotemporal distribution of energy consumption are output.

[0107] Based on the simulation results of the spatiotemporal distribution of energy consumption and the pre-collected observation data of the spatiotemporal distribution of energy consumption, the parameters of the urban energy modeling model CEA are adjusted until the loss between the simulation results of the spatiotemporal distribution of energy consumption output by the urban energy model CEA and the observation data of the spatiotemporal distribution of energy consumption is within a preset loss threshold range, thereby obtaining the urban energy system.

[0108] (4) The construction process of an urban water supply system includes:

[0109] Initialize the parameters of the urban water supply system (such as EPANET); for example, set the time step, simulation duration, and initial conditions of the urban water supply system. These initial conditions include, but are not limited to: node (user, enterprise) water supply pressure / demand, and water supply pipeline flow rate.

[0110] The river network data, water source data, water demand data, and network operation control data are input into the initialized urban water supply system EPANET for simulation operation, and the water supply simulation results are output; the water supply simulation results include time series data of node pressure and water supply pipeline flow.

[0111] Based on the water supply simulation results and the pre-collected urban surface water supply observation data (including historical time series data of node pressure and water supply pipeline flow), the parameters of the urban water supply system EPANET are adjusted until the loss between the water supply simulation results output by the urban water supply system EPANET and the water supply observation data is within the preset loss threshold range, thus obtaining the urban water supply system.

[0112] (5) The construction process of urban transportation network system includes:

[0113] Initialize the parameters of a multi-agent traffic simulation model (such as MATSim); for example, set the time step, simulation duration, and initial conditions for the distributed hydrological model. These initial conditions include, but are not limited to: initial soil moisture content, soil humidity distribution, initial river water level / flow rate, and initial flow rate in stormwater pipes.

[0114] The urban transportation network system is simulated by inputting the population data, transportation network data, infrastructure data, and travel behavior data into the initialized multi-agent-based traffic simulation model MATSim, and the simulation results are output. The traffic simulation results include traffic flow data, such as the flow, speed, and congestion of each road.

[0115] Based on the traffic simulation results and the pre-collected traffic flow observation data, the parameters of the multi-agent traffic simulation model MATSim are adjusted until the loss between the traffic simulation results output by the multi-agent traffic simulation model MATSim and the traffic flow observation data is within a preset loss threshold range, thereby obtaining the urban traffic network system.

[0116] It should be noted that the embodiments of the present invention do not impose specific limitations on the method of calculating the loss between the output results of each model and the observed data. For example, mean squared error, mean absolute error, cross-entropy loss, etc. can be used. The construction process of urban energy system, urban water supply system, and urban transportation network system can be found in the above-mentioned urban river and stormwater pipe system and urban surface water simulation system, and will not be described in detail here.

[0117] This invention combines various types of water disasters (such as rainstorms, river floods, and ocean level changes) to model different urban systems. It can identify the effects and impacts of different types of water disasters on different urban systems, identify potential urban disaster risks, and provide more comprehensive information for disaster early warning.

[0118] As an optional embodiment, the coupling of the urban system model and the disaster chains of various types of water disasters to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters includes:

[0119] Establish a connection between the urban river and stormwater pipe system and the urban surface water simulation system to generate urban water circulation paths;

[0120] Establish a connection between the urban surface water simulation system and the urban energy system to generate an urban energy control path;

[0121] Establish a connection between the urban energy system and the urban transportation network system to generate a first urban traffic travel control path;

[0122] Establish a connection between the urban energy system and the urban water supply system to generate a first urban water supply control path;

[0123] Establish a connection between the urban surface water simulation system and the urban transportation network system to generate a second urban traffic travel control path;

[0124] Establish a connection between the urban surface water simulation system and the urban water supply system to generate a second urban water supply control path; establish a connection between secondary disasters in the disaster chain of various types of water disasters and various systems in the urban system model to generate urban secondary disaster impact paths;

[0125] Based on the urban system model, the urban water circulation path, the urban energy control path, the first urban traffic control path, the first urban water supply control path, the second urban traffic control path, the second urban water supply control path, and the urban secondary disaster impact path, the urban system disaster simulation model is generated.

[0126] Furthermore, establishing the connection between the urban river and stormwater pipe system and the urban surface water simulation system to generate urban water circulation paths includes:

[0127] Establish a connection between the water overflow node of the urban river and stormwater pipe system and the surface flow node of the urban surface water simulation system;

[0128] Establish connections between the surface water collection nodes of the urban surface water simulation system and the network nodes of the urban river and stormwater pipeline system.

[0129] In the operation of the urban river and stormwater pipeline system and the urban surface water simulation system, the urban water circulation path is formed through the water overflow node, the surface flow node, the surface water convergence node, and the pipeline node.

[0130] Furthermore, establishing the connection between the urban surface water simulation system and the urban energy system to generate an urban energy control path includes:

[0131] Establish a connection between the regional water depth detection node of the urban surface water simulation system and the power supply equipment control node of the urban energy system;

[0132] In the operation of the urban surface water simulation system and the urban energy system, a one-way urban energy control path is formed through the regional water depth detection node and the power supply equipment control node.

[0133] For example, after analyzing the secondary disasters caused by different types of water disasters (such as rainstorms, river floods, and ocean level changes) to the target city, a disaster chain is established. For instance, river floods can lead to landslides, rainstorms can lead to land subsidence, and sea-level rise can lead to flooding, storm surges, and astronomical tides. Based on the influence relationships between different disasters and the city, it can be determined that river floods, ocean level changes, storm surges, and astronomical tides will affect urban river channels and stormwater drainage systems; landslides will affect urban energy systems, urban transportation networks, and urban water supply systems; and rainstorms and land subsidence will affect urban surface water simulation systems, urban river channels, and stormwater drainage systems. Based on the influence relationships between these different disasters and the city, connections can be established between secondary disasters (such as landslides and land subsidence) in the disaster chains of each type of water disaster and various systems in the urban system model, generating the impact paths of urban secondary disasters.

[0134] It should be noted that the connection between major water disasters (such as rainstorm disasters, river floods, sea level rise, storm surges, astronomical tides, etc.) and urban systems in the disaster chains of various types of water disasters has been established when modeling the corresponding urban systems.

[0135] Afterwards, based on the influence relationship between various cities, the connection between various city systems is established. The specific process is as follows: (1) Establish a city water circulation path between the urban river and rainwater pipeline system SWMM and the urban surface water simulation system LISFLOOD to realize bidirectional water flow exchange between the urban river and rainwater pipeline system SWMM and the urban surface water simulation system LISFLOOD.

[0136] Specifically, connections are established between the overflow nodes of the urban river and stormwater pipe system SWMM and the surface flow connection nodes of the urban surface water simulation system LISFLOOD, as well as between the surface water convergence nodes of the urban surface water simulation system LISFLOOD and the pipe network nodes of the urban river and stormwater pipe system SWMM. This enables bidirectional water flow exchange through the overflow nodes, surface flow connection nodes, surface water convergence nodes, and pipe network nodes during the operation of the urban river and stormwater pipe system SWMM and the urban surface water simulation system LISFLOOD.

[0137] For example, when an overflow occurs at a water overflow node (such as a pipe or manhole) in the urban river and stormwater pipe system SWMM, the excess water (overflow) enters the surface flow junction node of the urban surface water simulation system LISFLOOD through the water overflow node, triggering the urban surface water simulation system LISFLOOD to perform surface flow simulation; when the surface water of the urban surface water simulation system LISFLOOD converges to the surface water convergence node (such as the location of a stormwater inlet or manhole), it can flow back into the pipe network node (such as a pipe) of the urban river and stormwater pipe system SWMM. The specific simulation process is as follows: The Urban River and Stormwater Pipeline System (SWMM) is updated to a certain time. When the water level of a certain overflow node (inspection well) in the Urban River and Stormwater Pipeline System exceeds the ground elevation (or the set overflow threshold), an overflow occurs. The overflow is used as the inflow boundary condition of the corresponding grid cell (i.e., the surface flow node) in the Urban Surface Water Simulation System (LISFLOOD). The Urban Surface Water Simulation System (LISFLOOD) iterates several times in 2D flow during this time period. The surface water head or rechargeable flow rate of each surface water convergence node at the final time is returned to the Urban River and Stormwater Pipeline System (SWMM).

[0138] (2) An urban energy control path was established between the urban surface water simulation system LISFLOOD and the urban energy system CEA to realize the one-way impact assessment of surface flooding on urban power supply facilities.

[0139] Specifically, a connection is established between the regional water depth detection node of the urban surface water simulation system and the power supply equipment control node of the urban energy system, so that a one-way urban energy control path can be formed through the regional water depth detection node and the power supply equipment control node during the operation of the urban surface water simulation system and the urban energy system.

[0140] For example, when the urban surface water simulation system detects that the water depth in a certain area exceeds a critical threshold during the simulation, it means that the power supply facilities in that area may be threatened by flooding. The urban surface water simulation system will transmit this water depth information to the power supply equipment control nodes of the urban energy system to modify the operating status of the corresponding power supply facilities (such as forced shutdown or power reduction), thereby reflecting the reduction in power supply capacity caused by flooding in subsequent urban energy system simulations. The specific simulation process is as follows:

[0141] The urban surface water simulation system updates to a certain time -> calculates and outputs the surface water depth of each grid cell (i.e., regional water depth detection node) -> compares the water depth at the location of the power supply facility with the warning threshold -> if the water depth exceeds the threshold, a "disaster" marker is generated -> writes the marker into the configuration file of the urban energy system, and switches the relevant power supply facilities to shutdown or low-power mode through the power supply equipment control node of the urban energy system -> restarts the urban energy system to obtain the urban energy supply results under flood conditions.

[0142] In the above-mentioned urban energy control path, the flooding results simulated by the urban surface water simulation system are only transmitted "one-way" to the urban energy system CEA. The simulation changes of the urban energy system CEA do not affect the subsequent water flow calculation of the urban surface water simulation system. This is a one-way coupling, which can quickly assess the potential impact and risk of surface flooding on the urban energy system.

[0143] (3) The first urban traffic travel control path between the urban energy system CEA and the urban transportation network system MATSim, so as to realize one-way information transmission between the urban energy system CEA and the urban transportation network system MATSim.

[0144] For example, when the City Energy System (CEA) updates its power supply data during the simulation, it can determine whether certain transportation infrastructure (such as traffic lights, charging stations, and public transportation hubs) is affected by insufficient power supply. Once it detects that normal power demand cannot be met, the CEA transmits this information to the traffic restriction control node of the City Transportation Network System (MATSim) through the traffic energy control node, and automatically modifies its road network or public transportation configuration file, causing the affected roads, stations, or routes to enter the corresponding restricted state. The specific simulation process is as follows:

[0145] The city's energy system (CEA) is updated to a certain point in time -> the real-time power supply coverage and available capacity of various areas of the city are calculated -> the power supply demand of transportation facilities is compared -> if a location or hub cannot maintain normal operation due to insufficient power, an "affected" flag is generated -> the flag is written into the city's transportation network system (MATSim) configuration through the coupling node, and the transportation infrastructure corresponding to the flag is modified to "restricted" or "out of service" status in the road network configuration or public transportation configuration file of the city's transportation network system (MATSim) -> the city's transportation network system (MATSim) restarts the simulation with the latest configuration -> the traffic flow and travel plans under the power supply constraint scenario are recalculated.

[0146] It is understandable that the coupling nodes between the urban energy system CEA and the urban transportation network system MATSim are public facilities and areas between the two systems (such as traffic lights, charging piles, public transportation hubs, etc.). Through the coupling nodes of the two systems, the first urban traffic travel control path can be established and information can be transmitted between the two systems.

[0147] In the aforementioned first urban traffic control path, since the power supply results of the urban energy system CEA are transmitted "one-way" to the urban traffic network system MATSim, changes in network or vehicle operation in traffic simulation by the urban traffic network system MATSim will not further affect the energy consumption calculation of the urban energy system CEA. This is a one-way coupling, which can quickly assess the potential impact and risks of power shortages on public transportation and road systems in urban emergency or extreme load scenarios.

[0148] (4) The first urban water supply control path between the urban energy system CEA and the urban water supply system EPANET realizes one-way information transmission between the urban energy system and the water supply network.

[0149] For example, once the City Energy System (CEA) updates to the latest power supply data, it can determine whether certain critical water supply facilities (such as pumping stations and water treatment plants) will be affected by insufficient power supply. If it detects that the power supply coverage cannot meet the facility's power demand, the CEA writes this result into its configuration file, causing the facility to enter a corresponding power reduction or shutdown state. The specific simulation process is as follows:

[0150] The city energy system CEA is updated to a certain point in time -> the available power coverage of each area is calculated and output to compare the power demand of water supply facilities -> if the power supply of a pumping station or water plant is insufficient, a "restricted" flag is generated -> the city energy system CEA configuration file is updated -> the facility corresponding to the flag is set to "partially operational" or "out of service" and saved to the operation status of the city energy system CEA -> the city water supply system EPANET obtains the facility status through the coupling node -> if the relevant pumping station is detected to be unable to supply power normally, the decrease in water supply capacity is reflected in its hydraulic calculation;

[0151] Similarly, the coupling nodes between the urban energy system CEA and the urban water supply system EPANET are common equipment between the two systems (such as pumping stations and water treatment plants). The first urban water supply control path can be established through the coupling nodes of the two systems to facilitate information transmission between the two systems.

[0152] In the aforementioned first urban water supply control path, the power supply results of the urban energy system CEA are only transmitted unidirectionally to the urban water supply system EPANET. The latter's updates to the hydraulic system will not affect the energy consumption calculation of the urban energy system CEA in turn. This is a unidirectional coupling, which can quickly assess the operational risks and water supply security of the water supply system under extreme urban power consumption scenarios.

[0153] (5) A second urban traffic travel control path between the urban surface water simulation system LISFLOOD and the urban traffic network system MATSim, realizing one-way information transmission between surface flooding information and urban traffic travel model.

[0154] For example, when the urban surface water simulation system LISFLOOD calculates the water depth in a certain area during the simulation, it determines whether it will affect traffic roads and public transportation hubs. Once it detects that the water depth exceeds a set threshold, LISFLOOD transmits this information to the urban transportation network system MATSim and updates the road network configuration accordingly (adjusting free-flow speeds or closing roads) and public transportation configuration (closing hubs or lines). The specific simulation process is as follows:

[0155] The LISFLOOD urban surface water simulation system updates to a certain time point -> calculates and outputs the surface water depth of each grid cell -> compares with the traffic network and hub locations: if the water depth of the grid where the road is located exceeds a set threshold, the free flow velocity of that road segment is reduced or it is marked as impassable in the road network configuration; if the water depth in the area where the public transportation hub is located is too high, it is set to be suspended in the public transportation configuration -> the updated content is written to the MATSim urban transportation network system configuration -> the configuration information corresponding to the affected road segments and stations is modified to "speed limit" or "shutdown", and saved to the network and bus route files of the MATSim urban transportation network system -> the MATSim urban transportation network system simulation is restarted: based on the updated network and public transportation configuration files, the traffic flow distribution and travel patterns under the flooding scenario are recalculated.

[0156] Similarly, the coupling nodes between the urban surface water simulation system LISFLOOD and the urban transportation network system MATSim are the common areas between the two systems (such as transportation networks and hub locations). Through the coupling nodes of the two systems, a second urban transportation travel control path can be established to facilitate information transmission between the two systems.

[0157] In the aforementioned second urban traffic control path, the inundation results of the urban surface water simulation system LISFLOOD are unidirectionally transmitted to the urban traffic network system MATSim. The latter's adjustments to traffic flow and travel plans do not further feed back to the surface water simulation process. This unidirectional coupling allows for rapid assessment of the potential impact on urban traffic and public transportation systems under urban flooding or waterlogging scenarios, and provides a reference for traffic management and emergency decision-making.

[0158] (6) A second urban water supply control path between the urban surface water simulation system LISFLOOD and the urban water supply system EPANET is established to realize one-way linkage between surface flooding information and water supply network.

[0159] For example, when the LISFLOOD urban surface water simulation system detects that the water depth in a certain area exceeds a specified threshold during the simulation, it indicates that the water supply facilities (such as pumping stations and water treatment plants) in that area may be threatened by flooding. The LISFLOOD system then transmits this information to the EPANET urban water supply system to reflect the impairment of water supply capacity. The specific simulation process is as follows:

[0160] The urban surface water simulation system LISFLOOD is updated to a certain time -> calculates and outputs the surface water depth of each grid cell -> compares the location of the water supply facility: if the water depth exceeds the threshold, the facility is marked as "flooded" or "degraded operation" -> writes this information into the urban water supply system EPANET: in the next stage of hydraulic calculation, the operation capacity of the flooded facility is limited or stopped.

[0161] Similarly, the coupling nodes between the urban surface water simulation system LISFLOOD and the urban water supply system EPANET are common equipment between the two systems (such as pumping stations and water plants). A second urban water supply control path can be established through the coupling nodes of the two systems to facilitate information transmission between them.

[0162] In the aforementioned second urban water supply control path, the flooding results of the urban surface water simulation system LISFLOOD are only transmitted unidirectionally to the urban water supply system EPANET, without feeding back the hydraulic or energy consumption calculation results to the surface water model. This is a unidirectional coupling, which can quickly assess the potential impact of flooding on the water supply system in flood scenarios and provide data support for urban disaster prevention, mitigation and emergency management.

[0163] This invention establishes bidirectional or unidirectional information transmission paths between various city systems to facilitate information transfer between different systems. The results of the simulation operation of one city system can be input into another city system, and further simulation can be performed by combining the input data. This ensures that the simulation of the city system is not only affected by a single disaster, but also integrates disaster data and the disaster results simulated by other city systems after the disaster, thereby ensuring the accuracy and timeliness of the city system simulation.

[0164] It should be noted that the simulation operation processes of the urban river and stormwater pipe system SWMM, the urban surface water simulation system LISFLOOD, the urban energy system CEA, the urban water supply system EPANET, and the urban transportation network system MATSim are existing technologies and will not be described in detail in the embodiments of this invention.

[0165] Furthermore, the method also includes:

[0166] Acquire data for predicting water disasters; wherein the data for predicting water disasters includes at least one of the following: data for predicting rainstorm disasters, data for predicting river floods, data for predicting ocean level changes, and data for predicting meteorological conditions.

[0167] The predicted water disaster data is input into the urban system disaster simulation model for simulation to obtain urban response strategies under the predicted water disaster data.

[0168] This invention, through coupling multiple water hazard chains within the urban river and stormwater drainage system (SWMM), urban surface water simulation system (LISFLOOD), urban energy system (CEA), urban water supply system (EPANET), and urban transportation network system (MATSim), ensures that the simulated operation of each urban system is affected by complex water hazards, rather than a single water hazard. Simultaneously, this coupling allows for mutual or unidirectional influence between the simulated urban systems, fully exploring the correlations between urban system models under various water hazard conditions. This achieves efficient integration of urban system models for multi-hazard simulations. The correlations between various urban systems and hazard chains in the urban system simulation model are as follows: Figure 2 As shown, this enables comprehensive simulation of urban disasters under various hazard factors such as extreme rainfall, river floods, storm surges, astronomical tides, and sea-level rise. A unified urban system simulation model coupling various urban systems has been constructed, achieving accurate simulation and comprehensive prevention and control strategy prediction under complex disaster chain scenarios. Subsequently, by inputting the predicted water disaster data into the urban system disaster simulation model for simulation, the simulation output results of each urban system under the predicted water disaster data can be obtained, thereby deriving urban response strategies. This effectively improves the accuracy of disaster evolution trend prediction and decision support capabilities for disaster emergency response.

[0169] See Figure 3 , Figure 3 This is a structural block diagram of a disaster chain-based urban system simulation model coupling device provided in an embodiment of the present invention. The disaster chain-based urban system simulation model coupling device includes a processor 11, a memory 12, and a computer program stored in the memory 12 and executable on the processor 11. When the processor 11 executes the computer program, it implements the steps in the above embodiments of the disaster chain-based urban system simulation model coupling method, such as steps S11 to S16.

[0170] For example, the computer program can be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 11 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the disaster chain-based urban system simulation model coupling device.

[0171] The disaster chain-based urban system simulation model coupling device may include, but is not limited to, a processor 11 and a memory 12. Those skilled in the art will understand that the schematic diagram is merely an example of a disaster chain-based urban system simulation model coupling device and does not constitute a limitation on the device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the disaster chain-based urban system simulation model coupling device may also include input / output devices, network access devices, buses, etc.

[0172] The processor 11 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 11 is the control center of the disaster chain-based urban system simulation model coupling device, connecting various parts of the device via various interfaces and lines.

[0173] The memory 12 can be used to store the computer programs and / or modules. The processor 11 implements various functions of the disaster chain-based urban system simulation model coupling device by running or executing the computer programs and / or modules stored in the memory 12 and calling the data stored in the memory 12. The memory 12 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 12 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0174] Wherein, if the modules / units integrated by the disaster chain-based urban system simulation model coupling device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 11, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0175] It should be noted that the working process of each module in the disaster chain-based urban system simulation model coupling device described in the embodiments of the present invention can refer to the working process of the disaster chain-based urban system simulation model coupling method described in the above embodiments, and the technical effect achieved is the same as that of the disaster chain-based urban system simulation model coupling method described in the above embodiments, and will not be repeated here.

[0176] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0177] The above description represents the preferred embodiments of the present invention. It should be noted that, for those skilled in the art, various improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A coupling method for urban system simulation models based on disaster chains, characterized in that, include: Collect city-related data and water disaster-related data; The city-related data are classified according to different city system types to obtain the first modeling data for different types of city systems; The water disaster-related data are classified to obtain second modeling data related to water disasters that affect the operation of different types of urban systems; Based on the first modeling data and the second modeling data of different types of urban systems, different types of urban system models are constructed; the urban system models include: urban river and stormwater pipe systems, urban surface water simulation systems, urban energy systems, urban transportation network systems, and urban water supply systems; Disaster chain analysis was performed on the aforementioned water disaster-related data to determine the disaster chains for each type of water disaster; The urban system model and the disaster chains of various types of water disasters are coupled to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters; The process of coupling the urban system model with the disaster chains of various types of water disasters to generate an urban system disaster simulation model that integrates the disaster chains of complex water disasters includes: Establish a connection between the urban river and stormwater pipe system and the urban surface water simulation system to generate urban water circulation paths; Establish a connection between the urban surface water simulation system and the urban energy system to generate an urban energy control path; Establish a connection between the urban energy system and the urban transportation network system to generate a first urban traffic travel control path; Establish a connection between the urban energy system and the urban water supply system to generate a first urban water supply control path; Establish a connection between the urban surface water simulation system and the urban transportation network system to generate a second urban traffic travel control path; Establish a connection between the urban surface water simulation system and the urban water supply system to generate a second urban water supply control path; Establish connections between secondary disasters in the disaster chains of various types of water disasters and various systems in the urban system model, and generate the impact paths of urban secondary disasters; Based on the urban system model, the urban water circulation path, the urban energy control path, the first urban traffic control path, the first urban water supply control path, the second urban traffic control path, the second urban water supply control path, and the urban secondary disaster impact path, the urban system disaster simulation model is generated.

2. The coupling method for urban system simulation models based on disaster chains as described in claim 1, characterized in that, The city-related data includes: urban topography data, river and pipeline network data, transportation network data, infrastructure data, land use data, soil data, building data, energy system data, geographic data, socio-economic data, population data, travel behavior data, water source data, water demand data, pipeline operation and control data, and overflow water volume data; the water disaster-related data includes: rainstorm disaster data, river flood data, ocean water level change data, and meteorological data.

3. The coupling method for urban system simulation models based on disaster chains as described in claim 2, characterized in that, The first modeling data for the urban river and stormwater pipe system includes: urban topography data, river network data, land use data, and overflow water volume data; the second modeling data for the urban river and stormwater pipe system includes: rainstorm disaster data, river flood data, and ocean water level change data. The method includes the following construction process for urban waterways and stormwater drainage systems: Initialize the parameters of the rainstorm and flood management model; The urban topography data, river network data, land use data, overflow water data, rainstorm disaster data, river flood data, and ocean water level change data are input into the initialized rainstorm flood management model for simulation, and the model simulation results are output. Based on the model simulation results and the pre-collected observation data of urban rivers and stormwater pipes, the parameters of the stormwater and flood management model are adjusted until the model simulation results output by the stormwater and flood management model and the loss of the observation data are within the preset loss threshold range, thereby obtaining the urban river and stormwater pipe system.

4. The coupling method for urban system simulation models based on disaster chains as described in claim 3, characterized in that, The first modeling data of the urban surface water simulation system includes: urban topography data, land use data, and soil data; the second modeling data of the urban surface water simulation system includes: rainstorm disaster data; the urban surface water simulation system is modeled using a distributed hydrological model based on the urban topography data, the river network data, the land use data, the soil data, and the rainstorm disaster data. The first modeling data for the urban energy system includes: building data, geographic data, energy system data, and socioeconomic data; the second modeling data for the urban energy system includes: meteorological data; the urban energy system is modeled using an urban energy modeling model based on the building data, geographic data, energy system data, socioeconomic data, and meteorological data. The first modeling data for the urban transportation network system includes: population data, transportation network data, infrastructure data, and travel behavior data; the urban transportation network system is modeled using a multi-agent-based traffic simulation model based on the population data, the transportation network data, the infrastructure data, and the travel behavior data. The first modeling data of the urban water supply system includes: river network data, water source data, water demand data, and network operation control data; the urban water supply system is modeled using a water supply network hydraulic and water quality simulation model based on the river network data, the water source data, the water demand data, and the network operation control data.

5. The coupling method for urban system simulation models based on disaster chains as described in claim 1, characterized in that, The process of establishing a connection between the urban river and stormwater pipe system and the urban surface water simulation system to generate urban water circulation paths includes: Establish a connection between the water overflow node of the urban river and stormwater pipe system and the surface flow node of the urban surface water simulation system; Establish connections between the surface water collection nodes of the urban surface water simulation system and the network nodes of the urban river and stormwater pipeline system. In the operation of the urban river and stormwater pipeline system and the urban surface water simulation system, the urban water circulation path is formed through the water overflow node, the surface flow node, the surface water convergence node, and the pipeline node.

6. The coupling method for urban system simulation models based on disaster chains as described in claim 1, characterized in that, The process of establishing a connection between the urban surface water simulation system and the urban energy system, and generating an urban energy control path, includes: Establish a connection between the regional water depth detection node of the urban surface water simulation system and the power supply equipment control node of the urban energy system; In the operation of the urban surface water simulation system and the urban energy system, a one-way urban energy control path is formed through the regional water depth detection node and the power supply equipment control node.

7. The coupling method for urban system simulation models based on disaster chains as described in claim 1, characterized in that, The method further includes: Acquire data for predicting water disasters; wherein the data for predicting water disasters includes at least one of the following: data for predicting rainstorm disasters, data for predicting river floods, data for predicting ocean level changes, and data for predicting meteorological conditions. The predicted water disaster data is input into the urban system disaster simulation model for simulation to obtain the urban response strategy under the predicted water disaster data.

8. A coupling device for a city system simulation model based on a disaster chain, characterized in that, include: A processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the disaster chain-based urban system simulation model coupling method as described in any one of claims 1 to 7.

9. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the urban system simulation model coupling method based on disaster chain as described in any one of claims 1 to 7.

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