A method for evaluating dynamic risk grade of secondary disasters related to typhoon rainstorm at village scale

Abstract

The application discloses a kind of village scale typhoon rainstorm related secondary disasters dynamic risk grade evaluation method, comprising: the geographical information database of the region to be studied is constructed, and the real-time disaster information of all types of buildings is obtained according to the real-time wind speed in a certain time range in the future, flooding situation.Economic total loss expectation value is used as the division index of risk grade with the number of village level disaster residence building, the number of evacuation population, when considering the flood secondary disasters and geological secondary disasters caused by typhoon rainstorm, respectively using uncoupling, coupling geological disaster residential building function evaluation framework is analyzed, the numerical value of each division index is obtained and is divided into corresponding grade.Cycle calculation is carried out with the update of meteorological forecast information.The present application is based on physical mechanism to deduce disaster, takes building function evaluation as core, and considers the uncertainty of meteorological forecast, building disaster-bearing capacity to carry out real-time dynamic risk grade evaluation for different kinds of secondary disasters.

Description

Technical Field

[0001] This invention relates to the field of typhoon and rainstorm disaster prevention and mitigation technology, and in particular to a method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale. Background Technology

[0002] Statistics show that my country's southeastern coastal provinces are affected by typhoons every year, making typhoon disaster prevention and early warning work crucial.

[0003] In disaster analysis, the causative factors (typhoon-rainstorm coupled disasters) and the disaster-bearing bodies (different types of buildings, infrastructure, etc.) are distributed unevenly in time and space, and therefore the impact on different regions also has spatial differences. In order to quantify this spatial heterogeneity of disaster impact, the patent document "A method for flood risk assessment and fine zoning based on random set theory" (CN111724033A) points out that risk assessment and zoning are important non-engineering measures.

[0004] The existing risk assessment system has the following problems: (1) The selection of risk indicators and the determination of the weight of each indicator are subjective (such as the analytic hierarchy process, principal component analysis, fuzzy hierarchical evaluation method, etc.), and cannot make an accurate assessment of the risk level from the perspective of physical mechanism; (2) Most existing risk assessment systems adopt a simple grid superposition method when considering the joint effect of multiple indicators, without considering the functional coupling relationship and interdependence of multiple infrastructure systems; (3) The existing flood risk zoning is mostly based on districts and counties as the basic unit of evaluation, which is not precise enough and cannot provide corresponding guidance for the specific implementation of emergency measures; (4) The occurrence of a certain disaster often leads to a "disaster chain" effect. For example, typhoon rainstorm disasters often trigger flood disasters, geological disasters (mudslides, landslides, etc.). The existing risk assessment system only considers single disasters and cannot consider the impact of secondary disasters caused by the disaster, making the assessment results inaccurate and incomplete. (5) The existing risk zoning system obtains the comprehensive risk over a long time series by considering a large number of disaster records in the region, but lacks an accurate assessment of the specific disasters that are about to occur. That is, it considers the overall nature of disaster risk but ignores the individual differences in the risk caused by a single disaster. This is specifically reflected in the fact that the weight of indicators in the evaluation system cannot take into account the uncertainty. Summary of the Invention

[0005] This invention aims to address the impending typhoon and rainstorm disasters by classifying the risk levels of different secondary disasters at the village level and dynamically updating the classification based on meteorological forecast data. This allows for a dynamic reflection of high-risk areas corresponding to various secondary disasters, providing a reference for decision-makers' emergency response.

[0006] The technical solution adopted to achieve the purpose of this invention is:

[0007] A method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale, characterized by comprising:

[0008] Step 1: Construct a geographic information database, which includes a natural information sub-database, a water network information sub-database, a power grid information sub-database, a building information sub-database, and a historical geological disaster information database.

[0009] Step Two: At the current time (before the disaster), use meteorological forecast products obtained from a high-resolution mesoscale weather forecasting model (such as the WRF model) to obtain hourly rainfall and wind speed forecasts for a certain future time period with spatially distributed differences in the study area. Use spatial interpolation techniques to obtain raster files of the rainfall and wind fields across the entire study area. Using rainfall as input, use a distributed hydrological model to obtain the time-history variation curves of total runoff in each sub-basin. Establish a two-dimensional hydrodynamic model for the sub-basin where residential buildings are located and calibrate the simulation parameters by referencing historical inundation scenarios. Based on the upstream and downstream relationships of the river channel, use the results of the hydrological model as input conditions, and simultaneously consider the rainfall situation in the sub-basin where residential buildings are located to perform flooding calculations, obtaining raster files of water depth distribution in the sub-basin where residential buildings are located at different times. Based on spatial relationships, extract the water depth and wind speed experienced by each power grid and water network node at different times, and the indoor and outdoor water depth experienced by all types of buildings at different times, adding them to the geographic information database described in Step One.

[0010] The indoor water depth value of a residential building is the water depth value of the grid (or water depth vector surface) that has a spatial intersection relationship with the residential building point file. The outdoor water depth value of a residential building is the average water depth value of the grid (or water depth vector surface) that intersects with the buffer zone created with a certain distance extended outward from the building. Note that it does not include the grid or water depth vector surface that intersects with the residential building point file. The water depth or wind speed value experienced by a power grid or water network node is the water depth value of the water depth grid (or water depth vector surface) or the wind speed value of the wind speed grid that has a spatial intersection relationship with the power grid or water network node point file.

[0011] Step 3: Define a functional assessment framework for residential buildings not coupled with geological hazards ( ) and the functional assessment framework for residential buildings coupled with geological hazards ( Based on this, functional assessment frameworks can be divided into single-story farmhouses and multi-story farmhouses according to building type. Each framework includes transportation, water supply, power supply and building subsystems. The water depth-average economic loss curves of different types of buildings are obtained using the Monte Carlo method.

[0012] Step 4: When considering secondary flooding disasters caused by typhoons and heavy rains, the method described in Step 3 shall be adopted. Using the disaster information obtained in step two as input, the following calculations are performed: Every residential building at all times Residential buildings in various functional states that consider the coupling of multiple systems probability ,in for Various states Category hour These represent "Full Functionality Status", "Advanced Functionality Restricted", "Basic Functionality Restricted", "Restricted Entry Status", and "Traffic Blockage Status", respectively. For different calculation times, Representing the A residential building, For the first The building is in Always in The probability value of a state is such that the sum of the probabilities of each building being in all functional states at any given time is 1. The functional state corresponding to the highest probability value is taken as the state. Time Architecture Functional state ,Right now When a building is in a "fully functional state," it indicates that its function is unaffected; when a building is in other functional states, it indicates that its function is affected to some extent. Buildings in other functional states are defined as residential buildings affected by secondary flood disasters, and the population contained in buildings in other functional states is defined as the flood-affected population. Then, based on the last moment... The functional status of each residential building at that time Statistics on the relationship between each residential building and the village-level administrative region, and the number of residential buildings affected by secondary floods in different village areas. Based on the functional time series values ​​of all residential buildings at different times, if a building is in a "restricted entry state," "building collapse state," or "traffic blockage state" at a certain time, then the population contained in that building is considered to be evacuated. If a residential building is in a "basic function restricted" state at a certain time, and the cumulative time in this state exceeds the prescribed critical time length, then the population contained in that building is also considered to be evacuated. Based on this, the number of people who should be evacuated due to secondary flooding disasters in different villages under a complete forecast scenario can be counted. Using the water depth-average economic loss curves for different types of buildings described in step three, and taking the disaster information obtained in step two as input, the expected average economic loss for each building (including all types, such as residential buildings, commercial buildings, and industrial buildings) at different times can be obtained. (For each building, if the water depth experienced at a certain time is less than the maximum water depth experienced at all previous times, then the maximum water depth experienced at all previous times is used.) The last forecast time is calculated based on the affiliation of each building with the village-level administrative region. Shicun Domain Expected total economic losses caused by secondary disasters of inland flooding ,Right now In the formula For architecture At the last forecast time The average expected economic loss at that time.

[0013] Step 5: When considering secondary geological disasters caused by typhoons and heavy rains, first adopt the approach described in Step 3. This framework not only considers the flood disaster information obtained in step two, but also the impact of secondary geological disasters. The effect is obtained by using the same calculation method and rules as in step four. Time of the first The residential building is located in various types probability and Time Architecture Functional state , among which when hour This represents the "building collapse state." When a building is in a "fully functional state," it indicates that its function is unaffected; when a building is in other functional states, it indicates that its function is affected to some extent. Residential buildings in other functional states are defined as residential buildings affected by coupled secondary disasters, and the population contained in these residential buildings is defined as the population affected by coupled secondary disasters. This is then based on the last forecast time. The functional status of each residential building at that time The statistics also include the relationship between each residential building and the village-level administrative region, and the number of residential buildings affected by coupled secondary disasters in different village areas. Based on the functional time series values ​​of all residential buildings at different times, if a building is in a "restricted entry state," "building collapse state," or "traffic blockage state" at a certain time, then the population contained in that building is considered to be evacuated. If a residential building is in a "basic function restricted" state at a certain time, and the cumulative time in this state exceeds the prescribed critical time length, then the population contained in that building is also considered to be evacuated. Based on this, the number of people who should be evacuated in different village areas under a complete forecast scenario can be counted. The difference between the number of residential buildings affected by secondary disasters and the number of residential buildings affected by flooding secondary disasters ( ); The number of residential buildings affected by secondary geological disasters is defined as the number of people who should be evacuated due to secondary disasters, coupled with the difference between the number of people who should be evacuated due to secondary disasters and the number of people who should be evacuated due to flooding secondary disasters. Defined as the number of people who should be evacuated due to secondary geological disasters.

[0014] Calculate the last predicted time Expected total economic loss caused by secondary geological disasters in a certain village First, through comparison The results obtained from the residential building function assessment framework that combines coupled and uncoupled geological hazards identified village areas. The collection of all residential buildings whose internal building functions have changed. Because a building's functional state changes to "collapsed state" during a secondary geological disaster, it can be considered that the value of all components contained in the entire building is lost. Calculate using the following formula:

[0015]

[0016] In the formula For architecture The sum of the values ​​of all components (including structural components) is numerically equal to the cumulative sum of the products of the average unit price and the quantity of each component. For architecture The last moment caused by secondary disasters from flooding The average expected economic loss, based on the construction The maximum water depth experienced and the water depth-average economic loss curves for the corresponding building type are determined under a complete forecast scenario.

[0017] Step Six: Using the number of affected residential buildings, the number of people to be evacuated, and the expected total economic loss as indicators for risk level classification, determine the weight of each indicator using the Analytic Hierarchy Process (AHP). For the two types of secondary disasters, the natural discontinuity classification method was used to classify the values ​​of each indicator from smallest to largest. The interval is used to determine the discontinuity point of each indicator under two types of secondary disasters. When the actual value of a certain indicator falls within the interval, the discontinuity point is determined. Score for each interval ( )for Therefore, the comprehensive scores of flood secondary disaster risk and geological secondary disaster risk in different villages under the current forecast scenario are determined. After calculating the scores for all villages, each village is divided into n intervals from smallest to largest based on its comprehensive score under each type of secondary disaster, using the natural discontinuity grading method, corresponding to level 1. The risk levels of secondary flood and geological disasters in different villages are determined, with higher levels indicating a more dangerous situation.

[0018] Step Seven: Repeat steps two through six at regular intervals until the distance between the study area and the typhoon center is less than a certain critical distance, at which point the study area has not yet been affected by the typhoon and its associated rainfall. The simulated typhoon and its associated rainfall scenario is dynamically updated using the updated forecast data. As the time of disaster approaches, the simulation results, the number of affected residential buildings, the number of people to be evacuated, and the expected total economic loss will gradually approach the actual results, and the dynamic risk level assessment for different villages will become increasingly accurate. Decision-makers can identify areas severely affected by various secondary disasters based on the forecasted risk levels, and thus implement disaster prevention measures such as resource allocation and personnel evacuation in advance according to the characteristics of each type of disaster. After the typhoon and its associated rainfall disaster has passed, the various observation data recorded by monitoring points within the risk prevention zone will be added to the historical geological disaster database to further improve the accuracy of predicting the probability of structural component damage under different disaster conditions.

[0019] Preferably, the natural information sub-database includes high-precision digital elevation data (DEM) of the study area, river system data, river cross-section data, land use type data, runoff data from hydrological stations, and historical flash flood scenario data, etc.; the water network information database includes pipeline topology, pipeline materials and lengths, total water head of water sources and water demand of each node; the power grid information data includes power grid topology, substation level, transmission and distribution line level and length, power plant unit capacity, load size of each user node, and spatial location of substations. The building information sub-database includes building physical information data (such as building outline, building type, geographical location, number of floors, building area, building foundation elevation, etc.) and building social information data (administrative divisions at all levels, family population in each residential building, etc.). The historical geological disaster information database includes (1) sample data recorded by monitoring points in each risk prevention zone. Each sample data includes the warning level, rainfall, cumulative rainfall recorded hourly, as well as the elevation, slope, land use type, and land cover type of the monitoring point. (2) data obtained by drone aerial photography hourly, including the number and type of residential buildings with structural component damage in each risk prevention zone. Based on this, the probability of damage to a certain type of residential building under different warning levels is calculated.

[0020] Preferably, when establishing the two-dimensional hydrodynamic model in step two, the terrain used should be modified according to the building foundation elevation information in the building information sub-database, that is, the building foundation elevation should be added to the elevation of the building location.

[0021] Preferably, in step three... , The feature is that the status of the included transportation subsystem can be divided into two types: "accessible" and "inaccessible"; the status of the included electronic power supply system and water supply subsystem can be divided into two types: "available" and "unavailable". The building subsystem includes the states of structural and non-structural components. Structural component states include "structural component damaged" and "structural component not damaged," while non-structural component states include "all components intact," "high-level functional components damaged," "basic functional components damaged," and "safety functional components damaged." This includes "Full Functionality Status", "Advanced Functionality Restricted", "Basic Functionality Restricted", "Restricted Access Status", "Building Collapse Status", and "Traffic Blockage Status". The building subsystem in the text only includes the status of non-structural components. The status of non-structural components includes "all components intact," "high-level functional components damaged," "basic functional components damaged," and "safety functional components damaged." The assessment framework includes "Full Functional Status," "Advanced Functional Restriction," "Basic Functional Restriction," "Restricted Access Status," and "Traffic Blockage Status." However, when applied to multi-story rural houses, the "Advanced Functional Restriction" status is not included in the non-structural component status section. "Advanced functions are limited" is not included because it is impossible for "advanced functions to be limited" in multi-story farmhouses.

[0022] Preferably, when the calculated outdoor water depth of a residential building exceeds the "accessibility threshold," the building's transportation subsystem is considered "inaccessible," and vice versa. Water and electricity supply systems are considered "available" when water and electricity are available, and "unavailable" otherwise. Structural components include walls. When the interpretation of drone aerial images reveals partial or complete collapse of the building, the structural components are considered "damaged," and vice versa.

[0023] According to Maslow's hierarchy of needs, the non-structural components are divided into advanced functional components, basic functional components, and safety functional components, which are used to realize the advanced, basic, and safety functions of residential buildings, respectively. Advanced functional components include air conditioners, computers, water heaters, etc. (for multi-story farmhouses, this refers only to such components on the top floor), mainly related to people's advanced needs such as comfort, work, and cleanliness; basic functional components include refrigerators, kitchen stoves, etc., mainly related to people's basic needs (food); safety functional components include bottom sockets, middle sockets, electronic switches, etc. (for multi-story farmhouses, this includes such components on each floor), mainly related to people's safety needs (risk of electric leakage under flood conditions).

[0024] The definitions of the four functional states of non-structural components vary depending on the availability of the "power supply system". When the "power supply system" is available, if all advanced functional components, basic functional components, and safety functional components are not damaged by flooding, the non-structural component is in the "all components intact state". When the basic functional components and (for multi-story farmhouses, the bottom floor) safety functional components are intact, and at least one advanced functional component is damaged, the non-structural component is in the "advanced functional component damaged state". For single-story farmhouses, when the safety functional components are intact and at least one basic functional component is damaged, or for multi-story farmhouses, when the top floor safety functional component is intact and at least one of the basic functional components and the bottom floor safety functional component is damaged, the non-structural component is in the "basic functional component damaged state". When at least one (for multi-story farmhouses, the top floor) safety functional component is damaged, the non-structural component is in the "safety functional component damaged state".

[0025] When the "power supply system" is unavailable, the building itself is in a power outage state. Therefore, whether the safety function components defined above are damaged is irrelevant to the safety function. The safety function is automatically satisfied when the "power supply system" is unavailable. At this time, non-structural components only include advanced function components and basic function components. The functional status of non-structural components only includes three types: "all components intact", "advanced function components damaged", and "basic function components damaged". When all advanced function components and basic function components are not damaged by flood, the non-structural component is in the "all components intact" state. When the basic function components are intact and at least one advanced function component is damaged, the non-structural component is in the "advanced function components damaged" state. When at least one basic function component is damaged, the non-structural component is in the "basic function components damaged" state.

[0026] The term "complete functional state" is defined as: a residential building possessing complete advanced, basic, and safety functions, capable of meeting residents' advanced, basic, and safety needs. The term "restricted advanced functions" is defined as: a residential building losing its complete advanced functions but still possessing basic and safety functions; in this state, it cannot meet residents' advanced needs but can meet their basic and safety needs. The term "restricted basic functions" is defined as: a residential building losing its basic functions but still possessing safety functions; in this state, it cannot meet residents' basic needs but can meet their safety needs. The term "restricted access state" is defined as: a residential building losing its safety functions, in which case it cannot meet residents' safety needs. The term "building collapse state" is defined as: a residential building whose structural components have been damaged. The term "traffic obstruction state" is defined as: a residential building where residents cannot safely wade out or enter due to outdoor water depth reaching a "critical access value."

[0027] Preferably, the The included contextual logical relationships are:

[0028] (1) When the traffic subsystem is in an "unreachable" state, The condition is described as "transportation blocked" because the building is currently surrounded by floodwaters, preventing people inside from leaving safely.

[0029] (2) When the transportation subsystem is "accessible" and the water and electricity supply systems are "available", if the non-structural components in the building subsystem are "all components in good condition", The condition is "fully functional"; if it is a non-structural component, it is "damaged advanced functional component". The condition is "Advanced functions are limited"; if it is not a structural component, it is "Basic functional components are damaged". The condition is "basic functions are limited"; if it is a non-structural component, it is "safety function component is damaged". This is a "restricted entry" state. This is because at this time, each component can receive external water and power supply support, and whether each component can function normally to achieve the building's advanced, basic, and safety functions depends solely on whether the component is physically damaged.

[0030] (3) When the transportation subsystem is “accessible”, the power supply subsystem is “available”, and the water supply subsystem is “unavailable”, if the non-structural components in the building subsystem are in the state of “all components are intact”, “advanced functional components are damaged”, or “basic functional components are damaged”, then the following conditions apply: All are classified as "basic functions limited" because the "kitchen stove" component cannot function when the water supply is interrupted; non-structural components are classified as "safety function components damaged". The area is in a "restricted entry" state, therefore there is a risk of electric leakage indoors at this time.

[0031] (4) When the traffic subsystem is "accessible" and the electronic supply system is "unavailable", All are classified as "limited basic functions" because the refrigerator, a basic functional component, will not function when the power supply is interrupted. According to research by the U.S. Department of Agriculture (USDA), food inside the refrigerator should be discarded after a 4-hour power outage. Therefore, it can be approximated that when the power is interrupted... When a building is deemed "unusable," the refrigerator, a key component of the building's basic structure, cannot function properly, resulting in the inability to meet people's dietary needs and the loss of its basic functions.

[0032] The aforementioned The included contextual logical relationships are:

[0033] (1) When the traffic subsystem is in an "unreachable" state, (1) When the structural component in the building subsystem is in the "traffic disruption state"; (2) When the structural component in the building subsystem is in the "structural component failure state", All are in the state of "building collapse"; (3) When the transportation subsystem is "accessible", the water and electricity supply system is "available", and the structural components in the building subsystem are "structural components are not damaged", if the non-structural components are "all components are intact", The condition is "fully functional"; if it is a non-structural component, it is "damaged advanced functional component". The condition is "Advanced functions are limited"; if it is not a structural component, it is "Basic functional components are damaged". The condition is "basic functions are limited"; if it is a non-structural component, it is "safety function component is damaged". (4) When the traffic subsystem is "accessible", the electronic supply system is "available", the water supply subsystem is "unavailable", and the structural components in the building subsystem are "structural components not damaged", if the non-structural components in the building subsystem are in "all components intact", "advanced functional components damaged", or "basic functional components damaged", the non-structural components in the building subsystem are in "all components intact", "advanced functional components damaged". All are classified as "basic functions limited"; if non-structural components are in a "safety function component damaged" state. (5) When the traffic subsystem is "accessible", the electronic system is "unavailable", and the structural components in the building subsystem are "structural components not damaged", All are listed as "basic functions limited".

[0034] Except for (2), the reasons for the occurrence of the other logical relationships are the same as those in the functional assessment framework for residential buildings without coupled geological hazards.

[0035] Preferably, to determine whether a component will fail under a certain disaster, it is first necessary to know the probability of failure or the distribution of relevant resistances of the component under different disaster conditions. For structural components, the following methods can be used:

[0036] A hybrid Naive Bayes model was established based on information from the historical geological disaster database. The information in the database includes (1) sample data recorded by real-time monitoring points in various geological disaster risk prevention zones throughout history. Each sample data includes the warning level recorded at the same time (no warning means level 0, and a warning may be issued at level 1). Level 4, corresponding to blue, yellow, orange and red warnings respectively), rainfall intensity (hourly rainfall), hourly cumulative rainfall, and the elevation, slope, land use type and land cover type of the monitoring point location. (2) Data obtained by drones on an hourly basis, including the number and type of residential buildings with structural component damage in each risk prevention zone.

[0037] The geological disaster risk prevention zone refers to the risk prevention zone set up in the national natural disaster risk survey. Each different geological disaster risk prevention zone has a real-time monitoring point, which is equipped with an automatic weather station to measure rainfall intensity and cumulative rainfall at different times. The warning level information of each prevention zone at different times is obtained by receiving push information issued by the meteorological bureau. Information such as the elevation, slope, land use type, and land cover type of the monitoring point is obtained through survey data or on-site measurement.

[0038] The dependent variable in the hybrid Naive Bayes model is the warning level, and the independent variables are various information from the database. After inputting the predicted rainfall time series data, the predicted warning levels for different future times can be obtained. Hourly aerial imagery data obtained by UAVs, after interpretation and statistical analysis, can be used to obtain warning levels at different warning levels. Within all geological disaster risk prevention zones Total number of residential buildings damaged Its total number of residential buildings of the corresponding type in all geological disaster risk prevention zones and warning level Total duration The ratio of the products (unit: hours) represents the different warning levels. The probability of damage to a residential building per hour, i.e. .

[0039] For non-structural components, the following method can be used: conduct a sampling survey of residential buildings in the study area to obtain a certain number of statistically significant samples. In each sample, the indoor water depth value (i.e., water depth resistance) and flooding time (the longest immersion time that can be withstood without damage, i.e., time resistance) that each type of non-structural component in the residential building should reach when it is damaged by water ingress should be recorded. The probability density functions of water depth resistance and flooding time resistance of various non-structural components can be obtained by fitting.

[0040] Preferably, in step four, the following method is used: Calculate the status of each residential building at different times under various conditions. The specific method for calculating the probability is as follows:

[0041] The probability density functions of water depth resistance and wind speed resistance of substations, power distribution rooms, and water pumps, as well as the probability density functions of water depth and inundation time resistance of power distribution poles, are obtained through experiments or relevant data. At the time when meteorological forecast data is available, samples are taken from all hydropower grid nodes, such as substations, power distribution rooms, and water pumps. Sub-depth resistance, extraction of all distribution poles Secondary wind speed resistance, by comparing the damage state of each node with the disaster experienced by each node at different times, can be obtained for each sampling at all times. Based on this, network flow analysis is used to perform functional analysis on the transmission network and the distribution network under each substation in the transmission network, obtaining the power supply status time series of each load node in the power grid. According to the physical damage state of all water pumps in the water network at different times and whether they are powered, the functional state of the water pumps is determined. Then, the water pressure driven analysis method is used to perform functional analysis on the water network to obtain the water supply percentage of each user node at different times. When it is greater than the water supply percentage threshold (e.g., 20%), the user node is considered to be able to be supplied with water; otherwise, it is not. Here, each load node and user node is a single building. Thus, the power supply percentage of each building is obtained. A combination of the state time series of the power supply and water supply subsystems;

[0042] At the moment when weather forecast data is obtained, the water resistance of each non-structural component of a residential building is measured and compared with the indoor water depth values ​​at all times to determine whether each non-structural component is damaged at different times (if the water resistance of a non-structural component is less than the indoor water depth experienced by the building at a certain time, it is considered damaged). The state of the non-structural components is determined, and this process is repeated. You can get it in one go. The state time series of non-structural components; initially disregarding the influence of the traffic subsystem, the state of the water supply, electricity supply systems, and non-structural components is used to obtain the state time series of each sampling point. The current state type is a certain building. exist Always in The probability of different functional types is the probability of a certain function at that moment. Number of times and The ratio, that is If at a certain moment the outdoor water depth of a building is greater than the "accessible critical value", then at that moment its Change the probability of being in a "traffic-blocked state" to 1, and the probability of being in any other state to 0; repeat the above operation for all buildings.

[0043] Application methods and The basic structure is the same, with the main difference being: (1) For residential buildings located in geological disaster risk prevention zones, the sampling of the structural components must be increased at each time. The method is to sample the probability of damage based on (1) the type of residential building and (2) the predicted value of the early warning level of the prevention zone at different times. The failure state of a structural component: For a residential building, if the state of a structural component in a certain sampling at a certain time is "structural component failure", then the structural component will remain in this state in subsequent times; (2) The application will display a "building collapse" state. , (1) If any water or power grid node or component fails at the current moment in a certain sampling, it will remain in the same state in subsequent moments in that sampling. (2) The time interval between two adjacent moments must be greater than or equal to the maximum flooding time resistance of the component with the smallest average water depth resistance among all types of non-structural components. Under this condition, the determination of the failure state of non-structural components can be reduced to a single variable determination, which can be achieved by comparing the water depth resistance and the indoor water depth value.

[0044] When applied to multi-story farmhouses , None of them contain any states related to "damaged advanced functional components".

[0045] Preferably, the method for obtaining the water depth-average economic loss curves for different types of buildings using the Monte Carlo method in step three is as follows:

[0046] First, determine the types of buildings within the study area (residential buildings, commercial buildings, industrial buildings, medical buildings, educational buildings, etc.). Then, through research, determine all components (excluding structural members) for each building type. The types and quantities of each type of building were determined through statistical surveys. The height required for flooding and destruction (Water depth resistance) and unit price From multiple samples, the corresponding water depth resistance probability distribution function is obtained. and unit price probability distribution function .

[0047] Using the Monte Carlo method based on the probability distribution function of water depth resistance For each Extract The resistance value at the next water depth, then the component ( ) at different water depths The following fragility curve It can be calculated using the following formula: In the formula for Among the water depth resistance values, those less than The quantity. Based on the unit price probability distribution function. Extraction using the Monte Carlo method Secondary components The single value of the component is used to determine its value. Average unit value Then when the water depth is Time component The average expected economic loss is , For components Quantity, buildings The average expected value of economic loss is the sum of all the values ​​it includes. The sum of the average expected economic losses, This is architecture. The water depth-average economic loss curve.

[0048] The construction in steps four and five At the last forecast time Expected value of average economic loss per hour The calculation method is as follows: , Buildings in a complete forecast scenario The maximum water depth experienced.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] By defining a functional assessment framework for residential buildings with both uncoupled and coupled geological hazards, the framework can consider the functional coupling relationship between building functions and water supply, power supply, and transportation systems at the building level, while also taking into account the uncertainty of component resistance. This allows for a more accurate assessment of the affected buildings, evacuated populations, and total economic losses caused by secondary floods and geological hazards. Furthermore, by effectively integrating geological hazard early warning level information into the building function assessment framework, the framework enables a more comprehensive consideration of overall risks. With the updating of weather forecasts and the realization of data-driven effects, decision-makers can identify areas severely affected by various secondary hazards based on the forecasted risk levels, thereby enabling them to implement disaster prevention measures such as resource allocation and personnel evacuation in advance, according to the characteristics of each type of hazard. Attached Figure Description

[0051] Figure 1 This is a flowchart of the method of the present invention.

[0052] Figure 2 This is a schematic diagram showing the village boundaries, geological disaster risk prevention zones, monitoring points within the prevention zones, and the distribution of various types of buildings in the study area.

[0053] Figure 3 (a) is a schematic diagram of the simulated indoor water depth experienced by a building at different times under the influence of a rainfall time series obtained from a certain forecast, and (b) is a schematic diagram of the wind speed time series experienced by a certain power distribution pole obtained from a certain forecast.

[0054] Figure 4 A functional assessment framework for residential buildings in single-story farmhouses that are not coupled with geological hazards.

[0055] Figure 5 A functional assessment framework for residential buildings in multi-story rural houses that are not coupled with geological hazards.

[0056] Figure 6 A functional assessment framework for residential buildings that are subject to coupled geological hazards and are applicable to single-story farmhouses.

[0057] Figure 7 A functional assessment framework for residential buildings that are compatible with geological hazards in multi-story rural houses.

[0058] Figure 8 This is a schematic diagram showing the functional coupling between various non-structural components and the power supply and water supply subsystems.

[0059] Figure 9 (a) A three-dimensional matrix diagram showing the functional status of each building and its subsystems at different times under each sampling result when applying the functional assessment framework for residential buildings without coupled geological hazards. Figure 9 (b) is a three-dimensional matrix diagram of each building's subsystems and functional status at different times under each sampling result when applying the residential building functional assessment framework coupled with geological hazards.

[0060] Figure 10 This is a schematic diagram of the water depth-average expected economic loss curve for a single-story farmhouse.

[0061] Figure 11 This is the risk level assessment result of secondary flood disasters in the study area, obtained from forecast data at a certain moment before the arrival of a typhoon.

[0062] Figure 12 This is the result of the geological secondary disaster risk level assessment for the study area, obtained from forecast data at a certain moment before the arrival of a typhoon. Detailed Implementation

[0063] This embodiment takes a village under the jurisdiction of Daoshi Town, Lin'an District as an example (e.g. Figure 2 The following describes the specific steps in the implementation process of this invention (as shown):

[0064] This embodiment discloses a dynamic risk level assessment method for secondary disasters related to typhoons and rainstorms at the village scale, such as... Figure 1 As shown, it includes the following steps:

[0065] Step 1: Using ArcGIS software, create a file-based geographic database (GDB file) to store information on all infrastructure systems, including sub-databases for natural information, water network information, power grid information, building information, and historical geological disaster information. The natural information sub-database should include high-precision digital elevation model (DEM) layer shapefiles for the entire study area, which can be obtained through lidar scanning or interpretation of remote sensing satellite imagery products; river system data shapefiles, which can be obtained through interpretation of remote sensing satellite imagery products; river cross-section data, which can be obtained through on-site measurement work; land use type data and soil type data, which can both be obtained through interpretation of remote sensing satellite imagery products; runoff data from hydrological stations, which can be obtained by consulting relevant records; the water network information database includes pipe network topology layer shapefiles, and the attribute tables should include attribute fields such as pipe material and length, total water head, and water demand at each node; the power grid information database includes power grid topology layer shapefiles detailed down to the substation level, and the attribute tables should include attribute fields such as substation level, transmission and distribution line level and length, power plant unit capacity, and load size at each user node. All of the above data can be obtained through literature surveys. The aforementioned building information sub-database includes shapefile layers containing building locations (outlines). The layer attribute table should include attribute fields such as structure type, geographical location, number of floors, building area, building foundation elevation, administrative division, and family population within each residential building. Water network information, power grid information, and building information can all be obtained through surveys.

[0066] Step two: At the current moment, use meteorological forecast products obtained from a high-resolution mesoscale weather forecasting model (such as the WRF model) to obtain the predicted hourly rainfall and hourly wind speed for the next 48 hours in the study area, which exhibit spatial distribution differences. Specifically, for the ncl format file output by WRF, use the nclread function in Matlab to read it, thus obtaining the rainfall and wind speed at different times for grid forecast points at different latitudes and longitudes. The spatial resolution of the obtained rainfall and wind speed is 5 km, and the temporal resolution is 1 hour.

[0067] After obtaining the wind speed and rainfall data for each forecast point, Python or ArcGIS software can be used to first interpolate the wind speed and rainfall values ​​at each forecast point at different times into a raster layer representing the wind speed and rainfall distribution over the entire area using the inverse distance weighting method or Kriging interpolation. The inverse distance weighting method is calculated using the following formula: , In the formula Let p be the attribute value of the point to be interpolated. The attribute value of point i. Let i be the weight of point i with respect to point p. Let p be the distance between points p and i. To control the parameters, Kriging interpolation is calculated using the following formula: In the formula This is the measurement value at the i-th position. The unknown weight at position i. The predicted value is N, where N is the number of points.

[0068] Based on data files such as the Digital Elevation Model (DEM) and land use types of the study area, sub-catchments were first delineated using the hydrological analysis module in ArcGIS or flood simulation software such as Mike. Raster layers of area rainfall at different times were used as input. During the process of converting rainfall into net runoff, the infiltration curve method and the fixed runoff coefficient method were used to calculate runoff generation for permeable and impermeable surfaces, respectively. This involved considering the evaporation, infiltration, and depression-filling effects of rainfall to obtain the net rainfall generated at different times. This data was then input into the runoff model, and the runoff process was calculated using the isochronous method to obtain the time-history variation curves of total runoff in each catchment area. For the sub-basin where residential buildings are located, a two-dimensional hydrodynamic model was established using software such as Mike or HEC-RAS, and calibrated by referencing historical inundation scenarios to adjust simulation parameters (such as the impact of different land use types on the flow). (The permeability coefficient, Manning coefficient, etc.) The DEM should be corrected based on the building base elevation information in the building information sub-database. That is, the building base elevation should be increased by 0.35m based on the elevation of the DEM raster that has a spatial intersection relationship with the building. The specific method is as follows: First, create a new field "num" in the building vector file in ArcGIS and assign it the value that each building needs to be raised. Then, use the feature to raster tool in ArcGIS to convert the building vector file to a raster, select the "num" field, and generate file 1. Use the raster calculator tool to assign all DEM pixel values ​​to zero and generate file 2. Then, use the mosaic to new raster tool to merge file 1 and file 2 to generate file 3. Finally, use the raster calculator tool to add file 3 and the original DEM file to obtain the DEM after the building elevation. Based on the upstream and downstream relationship of the river channel, the results of the hydrological model (production and confluence model) are used as input conditions. At the same time, the rainfall of the sub-basin where the residential building is located is considered. The two-dimensional shallow water wave equation is used to calculate the overflow, and the raster file or vector file of the water depth distribution of the sub-basin where the residential building is located at different times is obtained.

[0069] In ArcGIS software, the "Multi-value Extraction to Point" tool is used to extract the water depth, wind speed, and indoor water depth of each power grid and water network node at different times based on (1) the wind speed distribution raster layer and water depth distribution raster file at different times, and (2) the spatial location relationship. When extracting outdoor water depth, the rasterstats package in Python can be used. When the water depth distribution result is a vector file, the "Spatial Connection" tool can also be used for water depth extraction. Its form is as follows: Figure 3 As shown, these values ​​are added to the attribute table to form sub-databases for water network disaster information, power grid disaster information, and building disaster information. When extracting disaster information for residential buildings, the indoor water depth value for a given residential building is the average water depth of the raster cells that spatially intersect with the residential building's point file. The outdoor water depth value for a given residential building is the average water depth of the raster cells that intersect with the buffer zone created based on a certain distance from the building's point file (excluding raster cells intersecting with the residential building's point file). The water depth or wind speed experienced by a power grid or water network node is the water depth value of the water depth raster (or water depth vector surface) or the wind speed value of the wind speed raster that spatially intersects with the power grid or water network node's point file.

[0070] Step 3: Define the functional assessment framework for residential buildings with and without coupled geological hazards. and Each frame is designed for two types of residential buildings: single-story farmhouses and multi-story farmhouses, such as... Figure 4 , Figure 5 , Figure 6 , Figure 7 As shown. Its features include: the included transportation subsystem can be categorized into two states: "accessible" and "inaccessible." When the outdoor water depth of a residential building exceeds a "accessibility threshold," the building's transportation subsystem is considered "inaccessible," and vice versa. The "accessibility threshold" can be determined based on the movement speed of a person in water at a certain depth. When the movement speed of a person in water drops below a certain threshold, it indicates that people inside the building cannot leave on their own. Based on relevant research, 1m can be taken here. The included power supply and water supply subsystems can be categorized into two states: "available" and "unavailable." When a building can be supplied with water and electricity, the power supply and water supply subsystems are considered "available," and vice versa.

[0071] for The state of a building subsystem is divided into two parts: structural component state and non-structural component state. The structural component state includes two categories: "structural component failure" and "structural component not failure." The non-structural component state includes "all components intact," "high-level functional components damaged," "basic functional components damaged," and "safety functional components damaged." The functional state of a residential building considering multi-system coupling is also discussed. It is divided into "Full Functionality Status", "Advanced Functionality Restricted", "Basic Functionality Restricted", "Restricted Access Status", "Building Collapse Status", and "Traffic Blockage Status".

[0072] for The building subsystem does not include the state of structural components. The report does not include "the state of building collapse".

[0073] Structural components include walls. When a wall fails, the structural component is in a "structural component failed" state; when the wall does not fail, the structure is in a "structural component unfailed" state.

[0074] Based on my country's national conditions, multi-story rural houses typically have a living room, dining room, and kitchen on the first floor, while the second floor and above are mainly bedrooms and other rooms for various purposes. According to Maslow's hierarchy of needs, non-structural components are categorized into advanced functional components, basic functional components, and safety functional components. These are used to fulfill the advanced functions (meeting people's needs for comfort, office work, and cleanliness), basic functions (meeting people's basic needs (related to food), and safety functions (meeting people's safety needs, due to the risk of electrical leakage under flood conditions). Advanced functional components include air conditioners, computers, and water heaters (for multi-story rural houses, this refers only to these components on the top floor, as these components on each floor can meet advanced needs); basic functional components include refrigerators and kitchen stoves, which are located on the first floor in multi-story rural houses; safety functional components include bottom sockets, middle sockets, and electronic switches (for multi-story rural houses, this includes these components on each floor).

[0075] To determine whether a structural component will fail under a specific disaster, it is first necessary to know the probability of failure or the distribution of relevant resistance forces under different disaster conditions. For structural components, the following methods can be used:

[0076] First, a historical geological disaster database is established. The historical geological disaster database includes (1) sample data recorded by real-time monitoring points in all geological disaster risk prevention areas throughout history. Each sample data includes the warning level recorded at the same time (no warning means level 0, and a warning may be issued at level 1). Level 4, corresponding to blue, yellow, orange and red warnings respectively), rainfall intensity (hourly rainfall), hourly cumulative rainfall, and the elevation, slope, land use type and land cover type of the monitoring point location. (2) Data obtained by drones on an hourly basis, including the number and type of residential buildings with structural component damage in each risk prevention zone.

[0077] The geological disaster risk prevention zone mentioned above refers to the risk prevention zone established during the natural disaster risk survey. Figure 2 The image shows a risk prevention zone in a village in Daoshi Town, Lin'an District. Each geological disaster risk prevention zone has a real-time monitoring point equipped with an automatic weather station to measure rainfall intensity and cumulative rainfall at different times. The warning level information for each prevention zone at different times is obtained by receiving push notifications from the meteorological bureau. Information such as the elevation, slope, land use type, and land cover type of the monitoring point is obtained through survey data.

[0078] A mixture Naive Bayes model was trained using Python software based on sample data. The independent variables in the samples to be classified were rainfall intensity (hourly rainfall), hourly cumulative rainfall, and the elevation, slope, land use type, and land cover type of the monitoring point location. The dependent variable was the warning level (0 < ... 4) Conditional probabilities are calculated using a Gaussian Bayes model for numerical independent variables and a multinomial Bayes model for discrete independent variables, as shown in the following equation:

[0079]

[0080] In the formula This indicates that when the warning level is Time One independent variable ( The value of ) is The probability ( Represent the independent variable Divided into the first The type or take the first (number of values) For the training data belonging to The independent variable of the grade The mean, For the training data belonging to The independent variable of the grade The standard deviation. The warning level is indicated as independent variable Pick The number of samples, The warning level is The number of samples, The smoothing coefficient can be set to 1. This indicates the number of warning levels; in this case, it is 5.

[0081] The hourly rainfall information for each geological disaster risk prevention zone is identical to the rainfall information of the Thiessen polygon (generated based on rainfall forecast points) where the monitoring points are located within the zone. The value or type of each variable can be used to determine... A certain defense zone at all times Probability of being at different warning levels:

[0082]

[0083] In the formula Indicates in Constant vigilance zone The first independent variable of the internal monitoring point is taken as... When the maximum is reached The value serves as the defense zone at that moment. The warning level can be determined by interpreting and statistically analyzing hourly aerial imagery data obtained from drones, which is then used to determine the different warning levels. Within all geological disaster risk prevention zones Total number of residential buildings damaged Its total number of residential buildings of the corresponding type in all geological disaster risk prevention zones and warning level Total duration The ratio of the products (unit: hours) represents the different warning levels. The probability of damage to a residential building per hour, i.e. .

[0084] For non-structural components, the following method can be used: A sampling survey of residential buildings within the study area is conducted to obtain a statistically significant number of samples. For each sample, the indoor water depth (i.e., water depth resistance) and immersion time (the longest immersion time that can be withstood without damage, i.e., time resistance) that each type of non-structural component should reach when it experiences water ingress should be recorded. The probability density functions of water depth resistance and immersion time resistance for various non-structural components are then fitted to obtain the results. The distribution of water depth resistance for various types of non-structural components was determined through investigation and experimentation. and the distribution of resistance during flooding time All conform to a truncated normal distribution, and the parameters are shown in the table below (taking a single-story farmhouse as an example, with the indoor floor level of the first floor as the reference):

[0085]

[0086] For multi-story farmhouses, in addition to the basic functional components, all other components are provided on each floor, and their water resistance is increased by ((number of floors - 1)) based on the table above. Floor height).

[0087] The definitions of the four functional states in non-structural components vary depending on the availability of the "power supply system," such as... Figure 4 As shown in Figure 7, when the "power supply system" is available, and when all advanced functional components, basic functional components, and safety functional components are not damaged by flooding, the non-structural components are in a "completely intact state"; when the basic functional components and (for multi-story farmhouses, the bottom floor) safety functional components are intact, and at least one advanced functional component is damaged, the non-structural components are in a "damaged advanced functional component state." Since this situation is impossible for multi-story farmhouses—that is, when the basic functional components and safety functional components of the first floor are intact, the advanced functional components of the top floor cannot be damaged—therefore, in... Figure 5 , Figure 7 The "damaged advanced functional components" status has been removed from the non-structural component status list. For single-story farmhouses, when safety functional components are intact but at least one basic functional component is damaged, or for multi-story farmhouses, when the top floor safety functional component is intact but at least one basic functional component or the bottom floor safety functional component is damaged, the non-structural component is in the "damaged basic functional component" status. This is because when a socket at the bottom of the first floor is damaged, the circuit will short-circuit, and the basic functional component will also be unusable. Residents can then move to the top floor for safety. Therefore, the non-structural component is in the "damaged basic functional component" status. When at least one (or the top floor for multi-story farmhouses) safety functional component is damaged, the non-structural component is in the "damaged safety functional component" status. This is because for multi-story farmhouses, when the bottom floors are flooded, residents can move to the top floor for safety.

[0088] When the "power supply system" is unavailable, the building itself is in a power outage state. Therefore, whether the safety function components defined above are damaged is irrelevant to the safety function. The safety function is automatically satisfied when the "power supply system" is unavailable. At this time, non-structural components only include advanced function components and basic function components. The functional status of non-structural components only includes three types: "all components intact", "advanced function components damaged", and "basic function components damaged". When all advanced function components and basic function components are not damaged by flood, the non-structural component is in the "all components intact" state. When the basic function components are intact and at least one advanced function component is damaged, the non-structural component is in the "advanced function components damaged" state. When at least one basic function component is damaged, the non-structural component is in the "basic function components damaged" state.

[0089] The term "complete functional state" is defined as follows: a residential building possesses complete advanced, basic, and safety functions, meeting the residents' advanced, basic, and safety needs. The term "restricted advanced functions" is defined as follows: a residential building has lost its complete advanced functions but still possesses basic and safety functions; it cannot meet the residents' advanced needs but can meet their basic and safety needs. The term "restricted basic functions" is defined as follows: a residential building has lost its basic functions but still possesses safety functions; it cannot meet the residents' basic needs but can meet their safety needs. The term "restricted access state" is defined as follows: a residential building has lost its safety functions and cannot meet the residents' safety needs. The term "building collapse state" is defined as follows: the structural components of the residential building are damaged. The term "traffic obstruction state" is defined as follows: the residential building is unable to safely wade out or enter due to outdoor water depth reaching a "critical access value."

[0090] like Figure 4 , Figure 5 , Figure 6 , Figure 7 As shown, combined with Figure 8 The functional coupling relationship between water, electricity, and various non-structural components shown in the diagram indicates that, for single-story farmhouses... (1) When the traffic subsystem is in an "unreachable" state, (2) When the traffic subsystem is in the "accessible" state and the structural components of the building subsystem are in the "structural component failure state", regardless of the function of other subsystems, All are in the state of "building collapse". (3) When the transportation subsystem is "accessible", the water and electricity supply system is "available", and the structural components in the building subsystem are "structural components are not damaged", if the non-structural components are "all components are intact", This indicates a "fully functional state." If a non-structural component is in a "damaged advanced functional state," then... If the non-structural component is in a "restricted advanced function" state, it means that the component is in a "damaged basic function state". If the non-structural component is in a "damaged safety function component" state, then the basic function is limited. When the system is in a "restricted entry state", each component can receive external water and power supply support. Whether each component can function normally to achieve the advanced, basic, and safety functions of the building depends solely on whether the component is physically damaged. (4) When the traffic subsystem is "accessible", the power supply system is "available", the water supply subsystem is "unavailable", and the structural components in the building subsystem are "undamaged", when the non-structural components are in a "complete state", "damaged state of advanced functional components", or "damaged state of basic functional components", All are "basic functions limited" because, according to Figure 8 It is evident that without water, the building still cannot meet people's dietary needs and lacks basic functionality; when non-structural components are in a "damaged safety function component state," The system is in a "restricted entry" state because there is a risk of leakage from the bottom socket. (5) When the traffic subsystem is "accessible", the power supply system is "unavailable", and the structural components in the building subsystem are in a "structural component undamaged" state, All are "basic functions limited" because, according to Figure 8 It is known that the refrigerator, a basic functional component, cannot function when the power supply is interrupted. According to research by the U.S. Department of Agriculture (USDA), food inside the refrigerator should be discarded after a 4-hour power outage. Therefore, it can be approximated that when the power is interrupted... When a building is deemed "unusable," the refrigerator, a key component of the building's basic structure, cannot function properly, resulting in the inability to meet people's dietary needs and the loss of its basic functions.

[0091] For use in multi-story farmhouses In applicable to single-story farmhouses Based on this, the "damage state of advanced functional components" in non-structural components and their Simply delete the phrase "house collapsed" in the text.

[0092] For single-story and multi-story farmhouses In the corresponding Based on this, remove the judgments related to the state of structural components and The "collapsed house" status is sufficient.

[0093] The method for obtaining water depth-average economic loss curves for different types of buildings using the Monte Carlo method is as follows: First, determine the types of buildings in the study area (such as residential buildings, commercial buildings, industrial buildings, medical buildings, educational buildings, etc.). Then, through field surveys, determine all components (excluding structural components) of each building type. The types and quantities of each component in various types of buildings were determined through statistical surveys. The height required for flooding and destruction (Water depth resistance) and unit price From multiple samples, the corresponding water depth resistance distribution and unit price distribution probability density function were obtained. and .

[0094] If the water depth resistance of a component is less than the water depth experienced at a certain moment, it will fail. Here, we take a single-story farmhouse in a residential building as an example (see...). Figure 2 Taking the black triangle in the image as an example, this was determined through research. The relevant information is shown in the table below (the first floor indoor floor level is used as the reference when calculating water resistance):

[0095]

[0096] Using the Monte Carlo method based on the probability distribution function of water depth resistance For each component ( Extraction The resistance value at the next water depth, then the component At different water depths The following fragility curve It can be calculated using the following formula: In the formula for Among the water depth resistance values, those less than The quantity. Based on the unit price probability distribution function. Extraction using the Monte Carlo method Secondary components The single value of the component is used to determine its value. Average unit value Then when the water depth is Time component The average expected economic loss is , The number of components, building The average expected value of economic loss is the sum of all the values ​​it includes. The sum of the average expected economic losses, This is the water depth-average economic loss curve for a single-story farmhouse, as shown below. Figure 10 As shown.

[0097] When calculating other types of buildings in the study area (such as...) Figure 2 The same method is used when calculating the water depth-average economic loss curve for the rhombus shown (representing other types of non-residential buildings).

[0098] Step 4: When using In order to calculate the various conditions of each residential building at different times, The probability of water depth resistance distribution in substations, power distribution rooms, and water pumps is obtained through experiments or relevant data (such as the MH-HAZUS flood model). This distribution follows a truncated normal distribution, and the parameters in the corresponding probability density function are shown in the table below.

[0099]

[0100] According to the "National Standard of the People's Republic of China: Circular Concrete Poles (GB / T 4623-2006)", the probability density function of wind speed resistance distribution for a typical distribution pole can be obtained. EachThe probability density functions of water depth and submersion time resistance distribution for non-structural components are shown in the aforementioned table; at the time when meteorological forecast data is obtained (e.g. Figure 3 (0:00 in the middle) refers to the extraction of water from all hydropower grid nodes such as substations, power distribution rooms, and water pumps. Sub-depth resistance, extraction of all distribution poles Secondary wind speed resistance, by comparing it with the disaster experienced by each node at different times, can yield the damage state of each node at all times under each sampling. Figure 3 (a) is a schematic diagram of simulated indoor water depth experienced by a building at different times. For example, the water depth extracted at 42:00 represents the water depth from 42:00 to 43:00, and so on; Figure 3(b) shows a schematic diagram of the wind speed experienced by a power distribution pole at different times. When the water depth or wind speed resistance of any hydroelectric power grid node is less than the water depth or wind speed experienced at a certain time, the node will be damaged. Based on this, network flow analysis (see Lee II EE, Mitchell JE, Wallace W A. Restoration of Services in Interdependent Infrastructure Systems: A Network Flows Approach[J]. IEEE Transactions on Systems, Man and Cybernetics, Part C(Applications and Reviews), 2007, 37(6): 1303–1317) is used to perform functional analysis on the transmission network and the distribution network under each substation in the transmission network, and to obtain the power supply status time series of each load node in the power grid (see Xue J, Mohammadi F, Li X, et al. Impact of transmission tower-line interaction to the bulk power system during hurricane[J]. ReliabilityEngineering & System Safety, 2020, 203: 107079.). Based on the physical damage status of all water pumps in the water network at different times and whether they are powered, the functional status of the water pumps is determined (see Adachi T, Ellingwood B R. Serviceability of earthquake-damaged water systems: Effects of electrical power availability and power backup). Systems on system vulnerability[J]. Reliability Engineering & System Safety, 2008, 93(1): 78–88.), followed by a water pressure-driven analysis method (see Tanyimboh TT, Templeman A B. Seamless pressure-deficient water distribution system model[J].Proceedings of the Institution of Civil Engineers - Water Management, 2010, 163(8): 389–396.) After performing functional analysis on the water network, the water supply percentage of each user node at different times is obtained. When it is greater than the water supply percentage threshold (such as 20%), the user node is considered to be able to supply water; otherwise, it cannot be supplied water. Here, each load node and user node is a single building, and thus the percentage of each building is obtained. A combination of the state time series of the power supply and water supply subsystems, such as Figure 9 (a) shows the first two layers of the three-dimensional matrix corresponding to each building (i.e., the state of the power supply and water supply subsystems at all times and in all sampling results);

[0101] At the moment when weather forecast data is obtained, the water resistance of each non-structural component of a residential building is measured and compared with the indoor water depth values ​​at all times to determine whether each non-structural component is damaged at different times (if the water resistance of a non-structural component is less than the indoor water depth experienced by the building at a certain time, it is considered damaged). Then, according to the aforementioned definition of the state of non-structural components, the state of the non-structural components is determined, and this process is repeated. You can get it in one go. The state time series of a non-structural component, such as Figure 9 (a) shows the third layer of the three-dimensional matrix corresponding to each building; without considering the influence of the traffic subsystem, the state of the water supply, power supply system and non-structural components is used to obtain the results at different times in each sampling. The type of state, such as Figure 9 (a) shows the fourth layer of the three-dimensional matrix corresponding to each building. exist Always in The probability of different functional types is the probability of a certain function at that moment. Number of times and The ratio, that is , hour These represent "Full Functional Status", "Advanced Functional Restricted", "Basic Functional Restricted", "Restricted Access Status", and "Traffic Blockage Status", respectively. If the outdoor water depth of a building exceeds the "Accessibility Criterion" at a certain moment, then at that moment... Change the probability of being in a "traffic-blocked state" to 1, and the probability of being in any other state to 0; repeat the above operation for all buildings.

[0102] At the same time, it should be noted that (1) if a node in the power supply or water supply subsystem, or a structural or non-structural component in the building subsystem, fails at the current moment during a certain sampling, then the node or component will remain in a state of failure in subsequent moments during that sampling. (2) The time interval between two adjacent moments should be greater than or equal to the maximum time resistance of the component with the smallest average water depth resistance among various types of non-structural components (advanced, foundation, and safety function components). Under this condition, the determination of the failure state of non-structural components can be reduced to a single variable determination, which can be achieved by comparing water depth resistance and water depth value. Taking the table given in step three as an example, the time interval between two adjacent moments during the calculation can be taken as 1 hour.

[0103] Take the functional state corresponding to the maximum probability value as Time Architecture Functional state ,Right now When a building is in a "fully functional state," it indicates that its function is unaffected; when a building is in other functional states, it indicates that its function is affected to some extent. Buildings in other functional states are defined as residential buildings affected by secondary flood disasters, and the population contained in buildings in other functional states is defined as the flood-affected population. Then, based on the last moment... The functional status of each residential building at that time Statistics on the relationship between each residential building and the village-level administrative region, and the number of residential buildings affected by secondary floods in different village areas. Based on the functional time series values ​​of all residential buildings at different times, if a building is in a "restricted entry" or "traffic-blocked" state at a certain time, the population inside that building is considered to be evacuated. If a residential building is in a "basic function restricted" state at a certain time, and the cumulative time in this state exceeds the prescribed critical time length, the population inside that building is also considered to be evacuated. Based on this, the number of people who should be evacuated due to secondary flooding disasters in different villages under a complete forecast scenario can be counted. Using the water depth-average economic loss curves for different types of buildings obtained in step three, and taking the disaster information obtained in step two as input, the expected average economic loss for each building (including all types) at different times can be obtained (for each building, if the water depth experienced at a certain time is less than the maximum water depth experienced at all previous times, then the maximum water depth experienced at all previous times is used). The last forecast time is calculated based on the affiliation of each building with the village-level administrative region. Shicun Domain Expected total economic losses caused by secondary disasters of inland flooding ,Right now In the formula For architecture At the last forecast time The average expected economic loss at that time, based on the building The maximum water depth experienced and the water depth-average economic loss curve for the corresponding building type are determined under a complete forecast scenario, i.e. .

[0104] Step 5: Application methods and The basic structure is the same, with the main difference being: (1) for residential buildings located in geological disaster risk prevention zones (such as...) Figure 2 As shown), at each time point, the probability of damage is increased based on the predicted warning level of the residential building type and its corresponding protection zone at different times, according to the predicted value. Second sampling, such as Figure 9 (b) shows the third layer of the three-dimensional matrix corresponding to each building. For a residential building, if the state of the structural component is "structural component failure" in a certain sampling at a certain time, then the structural component will remain in this state in subsequent sampling times. (2) Considering the building functional state of multi-system coupling, "building collapse state" may occur. ), that is, in Figure 9 (b) The fifth layer of the three-dimensional matrix corresponding to each building will show a "building collapse state".

[0105] When a building is in a "fully functional state," it indicates that its function is unaffected. When a building is in other functional states, it indicates that its function is affected to some extent. Residential buildings in other functional states are defined as residential buildings affected by coupled secondary disasters, and the population contained in these residential buildings is defined as the population affected by coupled secondary disasters. Subsequently, based on the last forecast time... The functional status of each residential building at that time The statistics also include the relationship between each residential building and the village-level administrative region, and the number of residential buildings affected by coupled secondary disasters in different village areas. Based on the functional time series values ​​of all residential buildings at different times, if a building is in a "restricted entry state," "building collapse state," or "traffic blockage state" at a certain time, then the population contained in that building is considered to be evacuated. If a residential building is in a "basic function restricted" state at a certain time, and the cumulative time in this state exceeds the prescribed critical time length, then the population contained in that building is also considered to be evacuated. Based on this, the number of people who should be evacuated in different village areas under a complete forecast scenario can be counted. The difference between the number of residential buildings affected by secondary disasters and the number of residential buildings affected by flooding secondary disasters ( ); The number of residential buildings affected by secondary geological disasters is defined as the number of people who should be evacuated due to secondary disasters, coupled with the difference between the number of people who should be evacuated due to secondary disasters and the number of people who should be evacuated due to flooding secondary disasters. Defined as the number of people who should be evacuated due to secondary geological disasters.

[0106] Calculate the last predicted time Expected total economic loss caused by secondary geological disasters in a certain village First, through comparison The results obtained from the residential building function assessment framework that combines coupled and uncoupled geological hazards identified village areas. The collection of all residential buildings whose internal building functions have changed. Because a building's functional state changes to "collapsed state" during a secondary geological disaster, it can be considered that the value of all components contained in the entire building is lost. Calculate using the following formula:

[0107]

[0108] In the formula For architecture The sum of the values ​​of all components (including structural components) is numerically equal to the cumulative sum of the products of the average unit price and the quantity of each component. Taking a single-story farmhouse as an example, the information of all components except structural components is as described in the aforementioned table. The information of the structural components is as follows:

[0109]

[0110] For architecture The last moment caused by secondary disasters from flooding The average expected economic loss, based on the construction The maximum water depth experienced and the water depth-average economic loss curves for the corresponding building type are determined under a complete forecast scenario.

[0111] Step Six: Using the number of affected residential buildings, the number of people to be evacuated, and the expected total economic loss as indicators for risk level classification, first use YAAHP software to determine the weight of each indicator based on the analytic hierarchy process (AHP). For the two types of secondary disasters, the natural discontinuity classification method was used in ArcGIS software to classify the values ​​of each indicator from smallest to largest. The interval is used to determine the discontinuity point of each indicator under two types of secondary disasters. When the actual value of a certain indicator falls within the interval, the discontinuity point is determined. Score for each interval ( )for In this embodiment, each indicator is divided into 3 levels, and the weight value and score of each indicator are shown in the table below:

[0112]

[0113]

[0114] Finally, the comprehensive scores for flood secondary disaster risk and geological secondary disaster risk in different villages under the current forecast scenario were calculated using the "Field Calculator" in ArcGIS software. After calculating the scores for all villages under this forecast scenario, each village is divided into five intervals (corresponding to level 1) based on its comprehensive score under each type of secondary disaster, using the natural discontinuity method from smallest to largest. 5. Determine the risk levels of secondary flooding and geological disasters for different villages. Higher levels indicate a more dangerous disaster situation. Figure 11 , Figure 12 As shown.

[0115] Step Seven: Repeat steps two through six at regular intervals until the distance between the study area and the typhoon center is less than a certain critical distance, at which point the study area has not yet been affected by the typhoon and its associated rainfall. The simulated typhoon and its associated rainfall scenario is dynamically updated using the updated forecast data. As the time of disaster approaches, the simulation results, the number of affected residential buildings, the number of people to be evacuated, and the expected total economic loss will gradually approach the actual results, and the dynamic risk level assessment for different villages will become increasingly accurate. Decision-makers can identify areas severely affected by various secondary disasters based on the forecasted risk levels, and thus implement disaster prevention measures such as resource allocation and personnel evacuation in advance according to the characteristics of each type of disaster. After the typhoon and its associated rainfall disaster has passed, the various observation data recorded by monitoring points within the risk prevention zone will be added to the historical geological disaster database to further improve the accuracy of predicting the probability of structural component damage under different disaster conditions.

Claims

1. A method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale, characterized in that, include: Step 1: Construct a geographic information database, which includes a natural information sub-database, a water network information sub-database, a power grid information sub-database, a building information sub-database, and a historical geological disaster information database; Step 2: At the current moment, use the WRF model system to obtain the hourly rainfall and wind speed of the forecast matrix, and combine spatial interpolation and hydrological and hydrodynamic models to obtain the wind speed and flood scenarios at different times; Add the water depth and wind speed experienced by each power grid and water network node at different times in the future, as well as the indoor and outdoor water depth disaster information experienced by all types of buildings at different times, to the geographic information database; Step 3: Define the functional assessment framework AF1 for residential buildings without coupled geological hazards and the functional assessment framework AF2 for residential buildings coupled with geological hazards. Both AF1 and AF2 include transportation, water supply, power supply and building subsystems. The building subsystems include some or all of the structural components and non-structural components. The water depth-average economic loss curves of different types of buildings are obtained using the Monte Carlo method. Step 4: When considering secondary flood disasters, use AF1 to calculate the functional state F of each residential building at different times, considering the coupling of multiple systems. b The probability is specifically as follows: a sampling survey is conducted on residential buildings within the study area to obtain a certain number of samples. The probability density functions of water depth resistance and inundation time resistance of various non-structural components are then fitted. The state of the non-structural components is then determined, and this process is repeated n times. simu n can be obtained in one step. simu The state time series of a non-structural component; Based on the states of the water supply, power supply systems, and non-structural components, F is obtained at different times in each sampling. b The state type of building i at time t is F. b The probability of different functional types is F at that moment. b Number of times With n simu The ratio, that is When m = 1, 2, 3, 4, 6, func(m) represents "Full Functional State", "Advanced Functional Restricted", "Basic Functional Restricted", "Restricted Access State", and "Traffic Blockage State", respectively; if the outdoor water depth of a building is greater than the "accessible threshold" at a certain moment, then its F at that moment... b The probability of being in a "traffic-blocked state" is changed to 1, and the probability of being in any other state is changed to 0; the above operation is repeated for all buildings to obtain the probability of each residential building being in any of the following states at different times: b The probability; take the functional state corresponding to the maximum probability value as the functional state of the building at that moment, and define the building in a non-"complete functional state" as a residential building affected by secondary flood disasters; If a building is in a state of "restricted access," "collapsed," "traffic blocked," or "basic functions limited" for a cumulative period exceeding the critical duration, then the population within it is considered to be evacuated. Based on the maximum water depth experienced by each building and the water depth-average economic loss curves for different types of buildings, the expected average economic loss for each building at different times can be obtained. Based on the results of the last forecast time and the entire forecast process, combined with zoning relationships, the total number of residential buildings affected by secondary flood disasters in each village area can be obtained. The total number of people N who should be evacuated due to secondary disasters caused by floods fp Expected total economic loss ; Step 5: When considering secondary geological disasters, AF2 is used with the same calculation method as in Step 4 to obtain the total number of affected residential buildings and the total number of people to be evacuated in each village area caused by coupled secondary disasters. Based on the maximum water depth experienced by each building, the water depth-average economic loss curves of different types of buildings, and whether structural components are damaged, the expected average economic loss of each building at different times is obtained. Based on the results of the entire forecasting process and combined with the zoning relationship, the expected total economic loss of each village area caused by coupled secondary disasters is obtained. For any village area, the difference between the total number of affected residential buildings, the total number of people to be evacuated, and the expected total economic loss caused by coupled secondary disasters and flooding secondary disasters is defined as the total number of affected residential buildings due to geological secondary disasters. Total number of people (N) to be evacuated due to secondary geological disasters cp -N fp ), Expected total economic losses from secondary geological disasters ; Step Six: Using the number of affected residential buildings, the number of people to be evacuated, and the expected total economic loss as indicators for risk level classification, determine the comprehensive scores of flood secondary disaster risk and geological secondary disaster risk for different villages under the current forecast scenario based on the analytic hierarchy process and the natural discontinuity classification method. Then, use the natural discontinuity method to classify the flood secondary disaster risk level and geological secondary disaster risk level of different villages. Step 7: Repeat steps 2 through 6 at set time intervals until the distance between the study area and the typhoon center is less than a certain critical distance; after the disaster passes, supplement the various data recorded by the monitoring points in the risk prevention area into the historical geological disaster database.

2. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 1, characterized in that: The natural information sub-database includes high-precision digital elevation data (DEM), river system, river cross-section, land use type, runoff of hydrological stations, and historical flash flood scenario data; the water network information sub-database includes pipeline network topology, pipeline material and length, total water head and water demand of each node; the power grid information sub-database includes power grid topology, substation level, transmission and distribution line level and length, power plant unit capacity, load size of each user node and spatial location of distribution room; the building information sub-database includes building physical information data and building social information data; the historical geological disaster information database includes (1) sample data recorded by monitoring points in each risk prevention zone, each sample data includes hourly recorded warning level, rainfall, cumulative rainfall, and elevation, slope, land use type, and land cover type of the monitoring point location; (2) data obtained by drone aerial photography hourly, including the number and type of residential buildings with structural component damage in each risk prevention zone.

3. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 1, characterized in that: In step three, the traffic subsystems in AF1 and AF2 are categorized into "accessible" and "inaccessible"; the power supply and water supply subsystems are categorized into "available" and "unavailable"; the building subsystems include some or all of the structural component status and non-structural component status, with the structural component status including "structural component damaged" and "structural component undamaged"; the non-structural component status includes some or all of the following: "all components intact", "advanced function components damaged", "basic function components damaged", and "safety function components damaged"; and the residential building functional status includes some or all of the following: "full function status", "advanced function restricted", "basic function restricted", "restricted access", "building collapsed", and "traffic obstruction".

4. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 3, characterized in that: The method includes the following judgment conditions: (1) When the outdoor water depth of a residential building exceeds the “accessibility threshold”, the transportation subsystem is in an “unaccessible” state; otherwise, it is in an “accessible” state. When water and electricity can be supplied, the water and electricity supply system is in an "available" state; otherwise, it is in an "unavailable" state. Structural components include walls. When a residential building partially or completely collapses, the structural components are in a "structural component failure" state; otherwise, they are in a "structural component not failure" state. (2) The non-structural components are divided into advanced, basic and safety functional components. Advanced functional components include air conditioners, computers and water heaters. For multi-story farmhouses, this refers only to the advanced functional components in the top floor. Basic functional components include refrigerators and kitchen stoves. Safety functional components include bottom sockets, middle sockets and electronic switches. For multi-story farmhouses, this includes the safety functional components in each floor. When the "power supply system" is available, if all advanced, basic, and safety functional components are intact, the non-structural components are in a "completely intact state"; for single-story farmhouses, if the basic and safety functional components are intact and at least one advanced functional component is damaged, or for multi-story farmhouses, if the basic functional components and the bottom safety functional component are intact and at least one advanced functional component is damaged, the non-structural components are in a "damaged advanced functional component state"; for single-story farmhouses, if the safety functional components are intact and at least one basic functional component is damaged, or for multi-story farmhouses, if the top safety functional component is intact and at least one basic functional component or the bottom safety functional component is damaged, the non-structural components are in a "damaged basic functional component state"; for single-story farmhouses, if at least one safety functional component is damaged, or for multi-story farmhouses, if at least one top safety functional component is damaged, the non-structural components are in a "damaged safety functional component state". When the "power supply system" is unavailable, if all advanced and basic functional components are not damaged by the flood, the non-structural components are in the "all components intact" state; if the basic functional components are intact and at least one advanced functional component is damaged, the non-structural components are in the "advanced functional component damaged" state; if at least one basic functional component is damaged, the non-structural components are in the "basic functional component damaged" state. (3) The advanced functions of a residential building refer to the ability to meet people's needs for comfort, office work, and cleanliness; the basic functions refer to the ability to meet people's basic dietary needs; and the safety functions refer to the ability to meet people's life safety needs. The "complete functional state" is defined as the state in which a residential building has complete advanced, basic, and safety functions. The "restricted advanced functions" is defined as the state in which a residential building has lost its complete advanced functions but still has basic and safety functions. The "restricted basic functions" is defined as the state in which a residential building has lost its basic functions but still has safety functions. The "restricted access state" is defined as the state in which a residential building has lost its safety functions. The "collapsed building state" is defined as the state in which the structural components of a residential building have been damaged. The "traffic obstruction state" is defined as the state in which a residential building is surrounded by floods.

5. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 1, characterized in that: The logical relationships contained in AF2 in step three are as follows: (1) When the traffic subsystem is in an "unreachable" state, F b (1) When the structural component in the building subsystem is in the "traffic disruption state"; (2) When the structural component in the building subsystem is in the "structural component failure state", F b All are in "building collapse state"; (3) When the traffic subsystem is "accessible", the water and electricity supply system is "available", and the structural components in the building subsystem are "structural components not damaged", if the non-structural components are respectively "all components intact", "advanced functional components damaged", "basic functional components damaged" and "safety functional components damaged", then F b The states are respectively "fully functional", "advanced functions restricted", "basic functions restricted", and "restricted access"; (4) when the traffic subsystem is "accessible", the power supply system is "available", the water supply subsystem is "unavailable", and the structural components in the building subsystem are "structural components not damaged", if the non-structural components in the building subsystem are in "all components intact", "advanced function components damaged", or "basic function components damaged", F b All are "basic functions limited"; if non-structural components are in "safety function component damaged state", F b (5) When the traffic subsystem is "accessible", the electronic system is "unavailable", and the structural components in the building subsystem are "structural components not damaged", F b All are listed as "basic functions limited"; The state AF1 does not include structural components, and its F b It does not include the "building collapse state", but the rest of the logical relationships are the same as AF2.

6. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 4, characterized in that: To determine whether structural and non-structural components will fail at a given time, a hybrid Naive Bayes model is constructed for structural components based on sample data from a historical geological disaster information database. Subsequently, based on the hourly and cumulative rainfall at a certain monitoring point obtained from forecasts, the different warning levels of the risk prevention zone where the monitoring point is located at different times are predicted. The probability of structural failure of a certain type of residential building at different times is obtained by combining the probability of damage to a certain type of building under different warning levels. For non-structural components, the probability density functions of water depth and flooding time resistance distribution of various non-structural components in residential buildings are obtained through sampling surveys and experiments on residential buildings in the study area.

7. The method for dynamic risk level assessment of secondary disasters related to typhoons and rainstorms at the village scale as described in claim 1, characterized in that: The method for obtaining the water depth-average economic loss curves for different types of buildings in step three is as follows: Determine the building types included in the study area, and for each type of building, identify all components except structural members. wos The type and quantity of each type of building were determined through statistical surveys, and each type of c within various building types was obtained. wos Water depth resistance, unit price probability density function, and Monte Carlo method for each c wos Extract c simu The resistance value at the next water depth is then used to determine the vulnerability curve Fr of component c at different water depths d. c (d) It can be calculated using the following formula: In the formula n failure For c simu The number of water depth resistance values ​​less than d; Based on the unit price probability distribution function F(v) c Extract v simu Calculate the unit value of component c and its average unit value. When the water depth is d, the expected average economic loss of component c is: n c Given the number of components c, the average expected economic loss of building i is the sum of all c components it contains. wos The sum of the average expected economic losses, .

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