Disaster risk assessment method based on two-dimensional index of compound event of external flood and internal waterlogging

Abstract

The application provides a disaster risk assessment method based on a two-dimensional index of external flood and internal waterlogging composite events, and relates to the technical field of composite flood and waterlogging disaster risk assessment. The method comprises the following steps: acquiring basic geographic, underlying surface, hydro-meteorological and water conservancy engineering data of the external basin and urban area of a target region; constructing and verifying a basin-urban coupled hydrological model based on time-varying gain theory; extracting flood and waterlogging processes according to simulation results, setting a threshold to select a composite event, and fitting marginal distributions respectively; establishing a joint distribution based on a Copula function, and constructing a two-dimensional index of fusion intensity and cause indicators; determining an index threshold according to the urban flood control and drainage capacity, and calculating disaster risk based on a risk-exposure-fragility framework. The application can simultaneously measure the overall intensity of the composite event and the relative action of internal and external disaster-causing factors, and realizes quantitative and comparable assessment of regional risk.

Description

Technical Field

[0001] This application relates to the field of composite flood disaster risk assessment technology, and in particular to a disaster risk assessment method based on a two-dimensional index of composite events of external floods and internal waterlogging. Background Technology

[0002] Under the influence of climate change, heavy rainfall is becoming more frequent and sudden. Riverside cities are affected by the combined impact of torrential rains and urban flooding, as well as external river floods. The destructive power of these combined events far exceeds that of floods caused by a single driving factor, exacerbating the risk of urban flooding and causing significant loss of life and property. The complex nature of urban flooding events significantly increases the difficulty of flood prevention, disaster reduction, and flood risk management. Effectively identifying the patterns of these events and conducting risk assessments is crucial for enhancing urban disaster resilience.

[0003] According to literature review, current methods for identifying the patterns of combined flood and urban waterlogging events often rely on simple statistical methods based on historical flood data or joint distribution probability statistical methods to analyze the joint distribution characteristics of urban rainstorms and river floods, such as flow and water level, encountered by combined flood and urban waterlogging events. There is a lack of effective indicators that comprehensively consider the intensity of combined events involving both external river floods and urban waterlogging, and it is difficult to clearly elucidate the relative roles of urban waterlogging and external river floods in these events. Furthermore, in terms of regional risk assessment, the hazard-exposure-vulnerability assessment method is generally followed. While numerous studies have been conducted on individual flood risk assessments, the lack of measures for the hazard intensity of combined flood and urban waterlogging events makes it difficult to compare the differences in risk between different regions at the basin or regional level. This hinders the risk assessment and comparison of combined flood and urban waterlogging events within a basin. Therefore, the assessment of combined disaster risks related to combined flood and urban waterlogging remains insufficient.

[0004] Based on this, it is still necessary to further develop a method for identifying urban flooding and waterlogging composite events and to design risk assessment algorithms. In view of the shortcomings of existing methods, this invention fully considers the physical processes of urban flooding and waterlogging on composite flood disaster events and proposes a two-dimensional index construction and risk assessment scheme for urban flooding and waterlogging composite events. Summary of the Invention

[0005] This application provides a disaster risk assessment method based on a two-dimensional index for combined external flood and internal waterlogging events. It aims to overcome the shortcomings of existing technologies, such as the lack of a unified intensity measurement index for combined external flood and internal waterlogging events, the difficulty in quantifying the interaction between internal and external water conditions, and the insufficient comparability of regional risk assessments. By coupling hydrological simulation, marginal distribution fitting, and Copula function, a two-dimensional index that can simultaneously characterize the overall intensity of the event and the relative contributions of internal and external disaster-causing factors is constructed. Based on this two-dimensional index and the hazard-exposure-vulnerability framework, a quantitative and comparable risk assessment is achieved, thereby providing a systematic technical means and decision-making basis for risk identification, refined management, and scientific prevention and control of combined floods in watersheds and cities.

[0006] This application provides a disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events, including:

[0007] Acquire relevant data on external watersheds and urban areas of the target region, including basic geographic information, underlying surface data, hydrological and meteorological data, and water conservancy project data;

[0008] Based on the relevant data, a catchment unit was established, and a watershed-city coupled hydrological process simulation model was constructed based on time-varying gain theory to conduct integrated simulation and verification of watershed and city runoff generation and confluence.

[0009] Based on the simulation results, data on the external river flood process and urban waterlogging process were extracted. Flood thresholds and waterlogging thresholds were set to select composite events of external flood and internal waterlogging. Marginal distribution fitting was performed on the external flood characteristic quantity and the internal waterlogging characteristic quantity to obtain the marginal distribution.

[0010] The joint distribution of external flood and internal waterlogging characteristics is established based on the Copula function, and a two-dimensional index of the combined external flood and internal waterlogging event is constructed based on the marginal distribution.

[0011] The threshold of the two-dimensional index is determined based on the city's flood control and drainage capacity, and the risk of a combined external flood and internal waterlogging event is calculated based on the hazard-exposure-vulnerability framework.

[0012] As a preferred technical solution, the basic geographic information includes topographic elevation data, river network vector data, hydrological and meteorological station data, spatial distribution data of water conservancy projects, and urban drainage zoning data; the underlying surface data includes land use data and soil data; the hydrological and meteorological data includes long-term flow data of external rivers, as well as long-term precipitation, temperature, humidity, wind speed, and radiation data within the basin and city; the water conservancy project data includes characteristic parameters of reservoirs, pumping stations, and culverts.

[0013] As a preferred technical solution, based on the relevant data, a catchment unit is established, and a watershed-city coupled hydrological process simulation model is constructed based on time-varying gain theory. The methods for integrated runoff generation and collection simulation of the watershed and city include:

[0014] Based on the aforementioned topographic elevation data, river network data, and urban drainage zoning, water catchment units integrating the watershed-urban system are delineated.

[0015] Within each catchment unit, runoff calculation units are divided according to the underlying land use type and soil type, and runoff calculation is performed based on time-varying gain theory. The runoff calculation includes the following formulas:

[0016] (1)

[0017] (2)

[0018] (3)

[0019] In the formula, This represents the change in soil moisture content. These are precipitation, evapotranspiration, surface water runoff, soil water runoff, and groundwater runoff, respectively. The time-varying gain current generation factor, This represents the water content of the upper saturated soil layer. This refers to the water content of the upper and lower soil layers. These are the soil water runoff and groundwater runoff coefficients, respectively. For slope, For the slope length, Field holding capacity These are the total unit area, the permeable area, and the impermeable area, respectively. The threshold for water storage depth in impermeable areas. The coefficient for not directly entering the drainage system;

[0020] Based on the topology of the catchment unit, runoff calculations are performed and coupled with water conservancy project scheduling operations to obtain the hydrological process simulation results of the entire basin-city system.

[0021] As a preferred technical solution, a watershed-city coupled hydrological process simulation model is constructed based on time-varying gain theory. The integrated verification of runoff generation and confluence for the watershed and city includes the following methods:

[0022] By comparing simulated runoff processes with measured runoff processes, and using efficiency coefficient, relative error, and correlation coefficient as evaluation indicators, the calculation formulas for each evaluation indicator are as follows:

[0023] (4)

[0024] (5)

[0025] (6)

[0026] In the formula, These are the efficiency coefficient, relative error, and correlation coefficient, respectively. These are measured flow and simulated flow, respectively. These are the measured and simulated values ​​of the average flow rate, respectively. These are the data sequence number and the total length, respectively.

[0027] As a preferred technical solution, based on the simulation results, flood process data of the outer river and waterlogging process data of the city are extracted. Flood thresholds and waterlogging thresholds are set to select composite events of external flooding and internal waterlogging. Marginal distribution fitting is then performed on the external flood characteristic quantities and the internal waterlogging characteristic quantities to obtain the marginal distributions, including:

[0028] Extract long-series data on external river flood flow processes and urban runoff and water accumulation processes from the simulation results;

[0029] The annual maximum flood peak flow sequence and urban runoff sequence were fitted using a generalized extreme value distribution, and theoretical frequency values ​​were selected as flood threshold and water accumulation threshold, respectively.

[0030] Based on the run theory, when the external river flood flow and the urban runoff both exceed their corresponding thresholds, it is identified as a combined external flood and internal waterlogging event, and the duration, external river flood peak flow and urban waterlogging peak value of each event are extracted.

[0031] The marginal distributions of the outer river flood peak and the urban waterlogging peak were fitted using univariate probability distributions, and the optimal marginal distribution function was selected using the AIC and BIC criteria.

[0032] As a preferred technical solution, the Copula function is expressed as follows:

[0033] (7)

[0034] In the formula, For Copula functions, These are the combined events of external flooding and urban runoff, specifically the external river floods and urban runoff. Let be the distribution function of floodwaters from the outer river and urban runoff. These are the distribution function expressions for floodwaters from the outer river and runoff from the city, respectively. These are the inverse function expressions of the distribution functions of external river floods and urban runoff, respectively. This is the expression for the joint distribution function;

[0035] The joint distribution function is constructed by selecting the optimal Copula model from multiple candidate Copula functions based on the AIC and BIC criteria.

[0036] As a preferred technical solution, based on the aforementioned marginal distribution, the calculation formula for the two-dimensional index of the combined external flood and internal waterlogging event is as follows:

[0037] (8)

[0038] (9)

[0039] (10)

[0040] In the formula, A two-dimensional index for combined external flooding and internal waterlogging events. This is an intensity index for combined external flooding and internal waterlogging events; the higher the value, the greater the risk of such events. As an indicator of the causes of combined external flooding and internal waterlogging events, Let be the standard normal function of the joint probability distribution. Let be the standard normal function of the probability distribution of floods in the outer river. Let be the standard normal function of the urban runoff distribution probability. These represent the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. It is the arctangent function. c0, c1, c2, d1, d2, and d3 are intermediate variables used to calculate the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. They are all constants.

[0041] As a preferred technical solution, based on the aforementioned causal indicators The value of [value] is used to classify the combined event of external flooding and internal waterlogging into four types: when [value] This was a low-level flood and low-waterlogging event; when This was a low-level flooding event followed by high-level waterlogging; when This was during a period of high flooding and waterlogging; when This was a period of high flooding and low waterlogging.

[0042] As a preferred technical solution, the threshold of the two-dimensional index is determined based on the city's flood control and drainage capacity, and the risk of a combined external flood and internal waterlogging event is calculated based on the hazard-exposure-vulnerability framework, including:

[0043] Based on the design values ​​corresponding to the urban flood control and drainage standards, the threshold combination of the two-dimensional index of the combined external flood and internal waterlogging event is determined;

[0044] Select combined external flooding and internal waterlogging events that exceed the aforementioned threshold combination;

[0045] The risk of external flooding and internal waterlogging is calculated using a hazard-exposure-vulnerability framework, and the calculation formula is as follows:

[0046] (11)

[0047] In the formula, To mitigate the risk of both external flooding and internal waterlogging, The average frequency of external flooding and internal waterlogging events. As an intensity index for combined external flooding and internal waterlogging events, To standardize urban population, The area of ​​the urban built-up area is standardized.

[0048] As a preferred technical solution, the flood control standard is a design flood that occurs once every 20 years or 50 years, and the drainage standard is an urban outdoor drainage design standard that occurs once every 3 years; the threshold combination is determined based on the corresponding positions of the design flood and design drainage in the two-dimensional index space.

[0049] The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events provided in this application has at least the following beneficial effects:

[0050] 1. This application constructs a two-dimensional index for combined external flooding and internal waterlogging events based on the coupling of urban external flooding and internal waterlogging. Compared with traditional combined event encounter analysis, it can not only measure the intensity of combined external flooding and internal waterlogging events in different cities, but also characterize the relative role of urban water accumulation and external river floods in combined events, providing a solid foundation for the objective identification of the patterns of combined external flooding and internal waterlogging events. In addition, the two-dimensional index constructed in this application can also be extended to the assessment of other combined disaster events.

[0051] 2. The risk assessment method based on the two-dimensional index of the combined external flood and internal waterlogging event proposed in this application can better realize the assessment and comparison of the combined disaster risks of external flood and internal waterlogging in different cities within the basin, and provide comprehensive scientific and technological support for flood control and disaster reduction of the basin-city coupled system. Attached Figure Description

[0052] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0053] Figure 1 A flowchart illustrating a disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events, provided for embodiments of this application;

[0054] Figure 2 This application provides a diagram illustrating the occurrence patterns of different types of combined external flooding and internal waterlogging events in its embodiments.

[0055] Figure 3The image shows the risk assessment results of combined external flooding and internal waterlogging events in various cities within the study area, provided for the embodiments of this application.

[0056] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0057] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0058] The collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0059] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0060] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0061] This application provides a disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events, such as... Figure 1 As shown, the disaster risk assessment method based on the two-dimensional index of the combined external flood and internal waterlogging events includes steps S10 to S50.

[0062] S10: Obtain relevant data on the external watershed and urban areas of the target region. The relevant data includes basic geographic information, underlying surface data, hydrological and meteorological data, and water conservancy project data.

[0063] It should be noted that the target area mentioned in this article refers to the spatial range comprised of the target city and the external river basins it relies on and is affected by. Specifically, the target area includes two core components: first, the urban area defined by the administrative or planning boundaries of the target city itself, which is the direct victim of urban flooding; and second, the catchment area that flows into the city's external rivers (such as lakes), i.e., the external watershed, which is the upstream source of water that triggers external floods. Together, they constitute a watershed-city coupled system, which is a complete geographical unit for simulating and risk assessing combined events of external floods and urban flooding. In practical applications, for example, if the target city is Changsha City in Hunan Province, then its corresponding target area is the urban area of ​​Changsha City and the related upstream areas such as the Dongting Lake basin, which flows into the Xiangjiang River (through Changsha).

[0064] In this embodiment, basic geographic information of the catchment area of ​​the river basin outside the city and the urban area is collected and organized, including topographic elevation data, river network vector data, hydrological and meteorological stations, spatial distribution of water conservancy projects, and urban drainage zoning data; underlying surface data includes land use data and soil data within the catchment area of ​​the river basin and the urban area; long-series flow observation data from hydrological stations outside the city; long-series data from meteorological stations in the river basin and the city, including air pressure, precipitation, temperature, humidity, wind speed, radiation, etc.; and characteristic parameters of water conservancy projects in the river basin, including reservoirs, pumping stations, culverts, etc.

[0065] In an exemplary embodiment, taking the Dongting Lake basin as an example, the collected data includes 30m resolution topographic elevation data of the Dongting Lake basin, river network vector data of the basin, 26 meteorological stations in the basin, and 4 hydrological stations including Xiangtan, Taojiang, Taoyuan, and Shimen; underlying surface data includes 1km resolution land use data and 1km resolution soil data of the Dongting Lake basin in 1980, 1990, 2000, 2010, and 2020; hydrological station data includes long-term daily flow observation data from 1960 to 2016, and meteorological station data includes long-term daily data on air pressure, precipitation, temperature, humidity, wind speed, and radiation from 1960 to 2016; water conservancy project data includes characteristic reservoir capacity and water level of large, medium, and small reservoirs in the Dongting Lake basin, and design flow of large pumping stations and sluice gates.

[0066] S20: Based on relevant data, establish catchment units and construct a watershed-city coupled hydrological process simulation model based on time-varying gain theory to conduct integrated simulation and verification of watershed and city runoff generation and confluence.

[0067] In step S20, based on the topography and underlying surface data of the watershed and urban area, catchment units are established, and a watershed-city coupled hydrological process simulation model is constructed based on time-varying gain theory to simulate and verify the integrated runoff generation and confluence of the watershed and the city. In some embodiments, step S20 includes the following steps S201-S204.

[0068] S201, based on topographic digital elevation data and river system data of the watershed and urban areas, combined with the drainage zoning of urban areas, divides the watershed-urban system into integrated catchment units. For each catchment unit, runoff calculation units are divided according to the underlying land use type, soil type data, and slope data. For the watershed calculation units, they are divided into sunny slopes and shady slopes. For the urban built-up area, runoff calculation units of different gradients are divided according to urban data and considering the impact of impermeable area of ​​building areas on runoff. Through the upstream and downstream runoff topology relationship of the catchment units, a water cycle network structure for simulating the runoff generation and confluence of the watershed-urban system is established.

[0069] S202, based on time-varying gain theory, calculates precipitation, evapotranspiration, surface water runoff, soil water runoff, groundwater runoff, and soil moisture content for each catchment unit. Evapotranspiration is calculated using a multi-source evaporation model including canopy interception, vegetation transpiration, and soil evaporation. Surface water runoff calculations include runoff from impervious and permeable areas. Soil water runoff and groundwater runoff are calculated using the linear reservoir method. The main calculation formulas for the time-varying gain hydrological process runoff simulation of the watershed-city coupling are as follows:

[0070] (1)

[0071] (2)

[0072] (3)

[0073] In the formula, This represents the change in soil moisture content. These are precipitation, evapotranspiration, surface water runoff, soil water runoff, and groundwater runoff, respectively. The time-varying gain current generation factor, This represents the water content of the upper saturated soil layer. This refers to the water content of the upper and lower soil layers. These are the soil water runoff and groundwater runoff coefficients, respectively. For slope, For the slope length, Field holding capacity These are the total unit area, the permeable area, and the impermeable area, respectively. The threshold for water storage depth in impermeable areas. The coefficient is used to prevent direct entry into the drainage system.

[0074] S203, based on the runoff calculation of the catchment units, and according to the characteristics of the catchment units, uses the unit hydrograph method or the kinematic wave method to calculate the internal runoff of the catchment unit for watershed calculation units. For urban catchment units, depending on the level of detail of the urban area data, when drainage network data is lacking, the unit hydrograph method or the kinematic wave method is used for runoff calculation; when main pipeline data is available, a generalized drainage network method can be used for internal runoff calculation of the catchment unit; and when detailed pipeline data is available, pipeline hydrodynamic methods can be used for calculation. Based on the river network topology diagram composed of the catchment units, river runoff calculations are performed step by step from upstream to downstream. The Muskingen method or the kinematic wave method is used for river runoff. If there are reservoirs, pumping stations, or sluice gates in the river, reservoir scheduling, pumping station, and sluice gate drainage calculations are performed separately until all river runoff calculations are completed, obtaining the hydrological process simulation results of the entire watershed-city system.

[0075] S204 compares simulated and measured hydrological elements such as runoff, uses efficiency coefficient, relative error, and correlation coefficient as model evaluation indicators, and combines optimization algorithms and manual parameter adjustment to calibrate model parameters and verify results.

[0076] (4)

[0077] (5)

[0078] (6)

[0079] In the formula, These are the efficiency coefficient, relative error, and correlation coefficient, respectively. These are measured flow and simulated flow, respectively. These are the measured and simulated values ​​of the average flow rate, respectively. These are the data sequence number and the total length, respectively.

[0080] In one exemplary embodiment, the Dongting Lake basin is divided into 158 catchment units, including nine important cities: Yongzhou, Hengyang, Zhuzhou, Changsha, Shaoyang, Yiyang, Huaihua, Changde, and Zhangjiajie. The runoff generation calculation units are divided according to soil type data and land use type data since 1980. At the same time, the major large and medium-sized water conservancy projects in the basin are considered to establish a water cycle network structure for the runoff generation and runoff simulation of the basin-city system. Based on historical hydrological and meteorological data, the runoff generation and runoff simulation and parameter calibration of the Dongting Lake basin are carried out. The runoff simulation results of the main stations are shown in Table 1.

[0081] Table 1 Simulation Results of Runoff Processes at Major Hydrological Stations

[0082]

[0083] S30: Based on the simulation results, extract the flood process data of the outer river and the waterlogging process data of the city, set the flood threshold and waterlogging threshold to select the composite event of external flood and internal waterlogging, and perform marginal distribution fitting on the external flood characteristic quantity and the internal waterlogging characteristic quantity respectively to obtain the marginal distribution.

[0084] In step S30, based on the model simulation results, data on the external river flood process and the urban waterlogging process are selected, flood and waterlogging thresholds are set to select the combined event of external flood and urban waterlogging, and marginal distribution characteristic analysis is performed on the external flood and urban waterlogging processes respectively.

[0085] In some embodiments, based on the results of watershed-city coupled hydrological simulation, long-series simulation data of urban external river flood flow process and urban runoff and water accumulation process are selected. After fitting the maximum flood peak flow and urban runoff sequence using the Generalized Extreme Value distribution (GEV), theoretical frequency values ​​close to the actual minimum annual maximum flood peak and urban runoff are selected as the thresholds for external river flood and urban water accumulation. Based on the run theory, a composite event of external flood and urban waterlogging is selected, that is, when the external river flood flow and urban runoff are both greater than the set threshold, it is defined as a composite event. The duration, urban water accumulation peak, and external flood peak flow of each composite event are analyzed and calculated to obtain long-series sample data of composite events over a period of time. Univariate probability distributions, including Gamma, Exponential, Lognormal, Extreme Value, Generalized Pareto Distribution (GPD), Generalized Extreme Value Distribution (GEV), Log-logistic, and Logistic, were used to fit the marginal distributions of external flood peaks and urban waterlogging peaks. The Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC) were used as evaluation criteria to select the optimal fitting marginal distribution function.

[0086] In an exemplary embodiment, long-series data of external river flood flow processes and urban runoff and water accumulation processes simulated by models were selected for nine cities in the Dongting Lake Basin, including Yongzhou, Hengyang, Zhuzhou, Changsha, Shaoyang, Yiyang, Huaihua, Changde, and Zhangjiajie. After fitting the maximum flood peak flow and urban runoff sequence of each city using the generalized extreme value distribution, the thresholds for external river floods and urban water accumulation were determined. Combining the run theory, a combined event of external flood and urban waterlogging was selected. Marginal distribution fitting was performed on the external flood peak flow and urban water accumulation peak for each city from 1960 to 2016. The optimal marginal distribution functions with the most occurrences among all cities were obtained as follows: the optimal marginal distribution of external river flood peak flow was the generalized Pareto distribution (GPD), and the optimal marginal distribution of urban runoff and water accumulation was the generalized extreme value distribution (GEV).

[0087] S40: Based on the Copula function, establish the joint distribution of external flood and internal waterlogging characteristics, and based on the marginal distribution, construct a two-dimensional index of the combined external flood and internal waterlogging event.

[0088] In step S40, a joint distribution of external floods and internal waterlogging is established based on the Copula function, and a two-dimensional index of the combined event of external floods and internal waterlogging is constructed based on the marginal distribution of external floods and internal waterlogging to analyze the patterns of the combined event of external floods and internal waterlogging.

[0089] In some embodiments, after obtaining the marginal distribution functions of the external flood and urban runoff processes in the combined event of external flood and internal waterlogging, their joint distribution is constructed based on two-dimensional Copula functions, including Gaussian Copula, Student t Copula, Clayton Copula, Gumbel Copula, Frank Copula, etc. The Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AlC) are used as evaluation criteria to select the optimal Copula model to establish the joint distribution function of the external flood and urban runoff processes in the combined event of external flood and internal waterlogging.

[0090] (7)

[0091] In the formula, For Copula functions, These are the combined events of external flooding and urban runoff, specifically the external river floods and urban runoff. Let be the distribution function of floodwaters from the outer river and urban runoff. These are the distribution function expressions for floodwaters from the outer river and runoff from the city, respectively. These are the inverse function expressions of the distribution functions of external river floods and urban runoff, respectively. This is the expression for the joint distribution function.

[0092] Based on the joint distribution function, the joint probability sequence of external river floods and urban runoff processes during historical flood seasons is calculated. The sequence is then standardized and normalized to obtain the intensity index of the compound flood and waterlogging event (CFW). m Simultaneously, the marginal distribution probability sequences of the peak flow of the external river flood and the peak urban waterlogging were standardized and normalized to obtain the compound flood and waterlogging factor (CFW), which reflects the relative contributions of urban waterlogging and external river flood in the combined event of external flood and internal waterlogging. f Based on intensity and causal indicators, a two-dimensional compound flood and waterlogging index (CFWI) was constructed. Based on this, the occurrence patterns of different types of compound flood and waterlogging events were analyzed, including frequency, duration, and intensity.

[0093] (8)

[0094] (9)

[0095] (10)

[0096] In the formula, A two-dimensional index for combined external flooding and internal waterlogging events. This is an intensity index for combined external flooding and internal waterlogging events; the higher the value, the greater the risk of such events. As an indicator of the causes of combined external flooding and internal waterlogging events, Let be the standard normal function of the joint probability distribution. Let be the standard normal function of the probability distribution of floods in the outer river. Let be the standard normal function of the urban runoff distribution probability. These represent the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. For the arctangent function, The intermediate variables, c0, c1, c2, d1, d2, and d3, are used to calculate the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. They are all constants with values ​​of c0=2.515517, c1=0.802853, c2=0.010328, d1=1.432788, d2=0.189269, and d3=0.001308, respectively.

[0097] In some embodiments, according to The following are four different types of coupled events involving external flooding and internal waterlogging: The flooding event was classified as low-level flooding and low-level waterlogging. The flooding event was characterized by low-level flooding and high-level waterlogging. The external flooding and internal waterlogging event was characterized by both high flooding and high waterlogging. The flooding event was characterized by high flooding and low waterlogging.

[0098] In an exemplary embodiment, Gaussian Copula, Student t Copula, Clayton Copula, Gumbel Copula, and Frank Copula are used to fit joint distributions. From these two-dimensional Copula functions, the optimal Copula function is selected as Frank Copula using the AIC and BIC criteria. Based on the preferred Copula function, the joint probability sequence and its marginal distribution sequence of combined external flooding and internal waterlogging events in nine cities in the Dongting Lake basin are calculated and standardized to obtain a two-dimensional index sequence of combined external flooding and internal waterlogging events for each city. Based on this, the occurrence pattern of combined external flooding and internal waterlogging events is analyzed, and events are classified into four different types according to the causal indicators of different roles of external flooding and internal waterlogging: low flood / low waterlogging, low flood / high waterlogging, high flood / high waterlogging, and high flood / low waterlogging. Figure 2 As shown, the frequency distribution of different types of combined external flooding and internal waterlogging events indicates that low-flood / low-waterlogging and high-flood / high-waterlogging events account for a large proportion in each city, around 30%-40%, while low-flood / high-waterlogging and high-flood / low-waterlogging events account for a relatively small proportion, around 10-20%. The intensity results for different types of combined external flooding and internal waterlogging events show that high-flood / high-waterlogging events have a higher average intensity of 1.36, low-flood / low-waterlogging events have a lower average intensity of -0.40, and high-flood / low-waterlogging and low-flood / high-waterlogging events fall between the two, averaging 0.64 and 0.67 respectively.

[0099] S50: Determine the threshold of the two-dimensional index based on the city's flood control and drainage capacity, and calculate the risk of combined external flooding and internal waterlogging events based on the hazard-exposure-vulnerability framework.

[0100] In step S50, a two-dimensional index threshold for combined external flooding and internal waterlogging events is determined based on the city's flood control and drainage capacity. A hazard-exposure-vulnerability method is then used to conduct an urban external flooding and internal waterlogging risk assessment. In some embodiments, based on the design flood and design drainage for the city's flood control and drainage at the current or planned level year, a combination of two-dimensional index thresholds corresponding to combined external flooding and internal waterlogging events is calculated. For different combinations of two-dimensional index thresholds, combined external flooding and internal waterlogging disaster events exceeding the two-dimensional index threshold combination are selected. The hazard-exposure-vulnerability method is then used to conduct an external flooding and internal waterlogging risk assessment at the current or planned level year. Hazard is measured by the two-dimensional index of combined external flooding and internal waterlogging events; a higher value indicates greater hazard. Exposure is measured by the standardized per capita GDP or population of each city; a higher value indicates higher exposure. Vulnerability is measured by the standardized built-up area of ​​each city; a lower value indicates greater vulnerability. The calculation formula is as follows:

[0101] (11)

[0102] In the formula, To mitigate the risk of both external flooding and internal waterlogging, The average frequency of external flooding and internal waterlogging events. As an intensity index for combined external flooding and internal waterlogging events, To standardize urban population, The area of ​​the urban built-up area is standardized.

[0103] In one exemplary embodiment, based on the current level annual flood control standard of 20 years or 50 years and the urban outdoor drainage design standard of 3 years as the threshold, a two-dimensional index threshold combination is determined for each city. Based on this, combined flood and waterlogging disaster events exceeding the two-dimensional index threshold combination are selected to assess the risk of combined flood and waterlogging disasters. Figure 3 As shown in the results, Huaihua and Zhuzhou have a higher risk of combined flooding and waterlogging disasters, followed by Hengyang and Zhuzhou. Shaoyang and Changsha have a relatively lower risk, while Yiyang, Changde, and Zhangjiajie have the lowest risk. Overall, the risk is lower in the northern region than in the southern region.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events, characterized in that, include: Acquire relevant data on external watersheds and urban areas of the target region, including basic geographic information, underlying surface data, hydrological and meteorological data, and water conservancy project data; Based on the relevant data, a catchment unit was established, and a watershed-city coupled hydrological process simulation model was constructed based on time-varying gain theory to conduct integrated simulation and verification of watershed and city runoff generation and confluence. Based on the simulation results, data on the external river flood process and urban waterlogging process were extracted. Flood thresholds and waterlogging thresholds were set to select composite events of external flood and internal waterlogging. Marginal distribution fitting was performed on the external flood characteristic quantity and the internal waterlogging characteristic quantity to obtain the marginal distribution. The joint distribution of external flood and internal waterlogging characteristics is established based on the Copula function, and a two-dimensional index of the combined external flood and internal waterlogging event is constructed based on the marginal distribution. The threshold of the two-dimensional index is determined based on the city's flood control and drainage capacity, and the risk of a combined external flood and internal waterlogging event is calculated based on the hazard-exposure-vulnerability framework.

2. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1, characterized in that, The basic geographic information includes topographic elevation data, river network vector data, hydrological and meteorological station data, spatial distribution data of water conservancy projects, and urban drainage zoning data; the underlying surface data includes land use data and soil data; the hydrological and meteorological data includes long-term flow data of external rivers, as well as long-term precipitation, temperature, humidity, wind speed, and radiation data within the basin and city; the water conservancy project data includes characteristic parameters of reservoirs, pumping stations, and culverts.

3. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1, characterized in that, Based on the relevant data, catchment units are established, and a watershed-city coupled hydrological process simulation model is constructed based on time-varying gain theory. The integrated simulation of runoff generation and collection for the watershed and city includes the following methods: Based on the aforementioned topographic elevation data, river network data, and urban drainage zoning, water catchment units integrating the watershed-urban system are delineated. Within each catchment unit, runoff calculation units are divided according to the underlying land use type and soil type, and runoff calculation is performed based on time-varying gain theory. The runoff calculation includes the following formulas: （1） （2） （3） In the formula, This represents the change in soil moisture content. These are precipitation, evapotranspiration, surface water runoff, soil water runoff, and groundwater runoff, respectively. The time-varying gain current generation factor, This represents the water content of the upper saturated soil layer. This refers to the water content of the upper and lower soil layers. These are the soil water runoff and groundwater runoff coefficients, respectively. For slope, For the slope length, Field holding capacity These are the total unit area, the permeable area, and the impermeable area, respectively. The threshold for water storage depth in impermeable areas. The coefficient for not directly entering the drainage system; Based on the topology of the catchment unit, runoff calculations are performed and coupled with water conservancy project scheduling operations to obtain the hydrological process simulation results of the entire basin-city system.

4. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1 or 3, characterized in that, Based on time-varying gain theory, a watershed-city coupled hydrological process simulation model is constructed. The methods for integrated verification of runoff generation and concentration in both the watershed and the city include: By comparing simulated runoff processes with measured runoff processes, and using efficiency coefficient, relative error, and correlation coefficient as evaluation indicators, the calculation formulas for each evaluation indicator are as follows: （4） （5） （6） In the formula, These are the efficiency coefficient, relative error, and correlation coefficient, respectively. These are measured flow and simulated flow, respectively. These are the measured and simulated values ​​of the average flow rate, respectively. These are the data sequence number and the total length, respectively.

5. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1, characterized in that, Based on the simulation results, flood process data from the outer river and waterlogging process data from the city were extracted. Flood thresholds and waterlogging thresholds were set to select composite events of external flooding and internal waterlogging. Marginal distribution fitting was performed on the external flood characteristic quantities and the internal waterlogging characteristic quantities to obtain the marginal distributions, including: Extract long-series data on external river flood flow processes and urban runoff and water accumulation processes from the simulation results; The annual maximum flood peak flow sequence and urban runoff sequence were fitted using a generalized extreme value distribution, and theoretical frequency values ​​were selected as flood threshold and water accumulation threshold, respectively. Based on the run theory, when the external river flood flow and the urban runoff both exceed their corresponding thresholds, it is identified as a combined external flood and internal waterlogging event, and the duration, external river flood peak flow and urban waterlogging peak value of each event are extracted. The marginal distributions of the outer river flood peak and the urban waterlogging peak were fitted using univariate probability distributions, and the optimal marginal distribution function was selected using the AIC and BIC criteria.

6. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1 or 5, characterized in that, The Copula function is represented as follows: （7） In the formula, For Copula functions, These are the combined events of external flooding and urban runoff, specifically the external river floods and urban runoff. Let be the distribution function of floodwaters from the outer river and urban runoff. These are the distribution function expressions for floodwaters from the outer river and runoff from the city, respectively. These are the inverse function expressions of the distribution functions of external river floods and urban runoff, respectively. This is the expression for the joint distribution function; The joint distribution function is constructed by selecting the optimal Copula model from multiple candidate Copula functions based on the AIC and BIC criteria.

7. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 6, characterized in that, Based on the aforementioned marginal distribution, the calculation formula for the two-dimensional index of the combined external flood and internal waterlogging event is as follows: （8） （9） （10） In the formula, A two-dimensional index for combined external flooding and internal waterlogging events. This is an intensity index for combined external flooding and internal waterlogging events; the higher the value, the greater the risk of such events. As an indicator of the causes of combined external flooding and internal waterlogging events, Let be the standard normal function of the joint probability distribution. Let be the standard normal function of the probability distribution of floods in the outer river. Let be the standard normal function of the urban runoff distribution probability. These represent the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. It is the arctangent function. c0, c1, c2, d1, d2, and d3 are intermediate variables used to calculate the joint distribution probability value, the external river flood probability value, and the urban runoff probability value, respectively. They are all constants.

8. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 7, characterized in that, According to the causal indicators The value of [value] is used to classify the combined event of external flooding and internal waterlogging into four types: when [value] This was a low-level flood and low-waterlogging event; when This was a low-level flooding event followed by high-level waterlogging; when This was during a period of high flooding and waterlogging; when This was a period of high flooding and low waterlogging.

9. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 1, characterized in that, The threshold of the two-dimensional index is determined based on the city's flood control and drainage capacity, and the risk of a combined external flood and internal waterlogging event is calculated based on the hazard-exposure-vulnerability framework, including: Based on the design values ​​corresponding to the urban flood control and drainage standards, the threshold combination of the two-dimensional index of the combined external flood and internal waterlogging event is determined; Select combined external flooding and internal waterlogging events that exceed the aforementioned threshold combination; The risk of external flooding and internal waterlogging is calculated using a hazard-exposure-vulnerability framework, and the calculation formula is as follows: （11） In the formula, To mitigate the risk of both external flooding and internal waterlogging, The average frequency of external flooding and internal waterlogging events. As an intensity index for combined external flooding and internal waterlogging events, To standardize urban population, The area of ​​the urban built-up area is standardized.

10. The disaster risk assessment method based on a two-dimensional index of combined external flooding and internal waterlogging events as described in claim 9, characterized in that, The flood control standard is a design flood that occurs once every 20 years or 50 years, and the drainage standard is a design standard for urban outdoor drainage that occurs once every 3 years; the threshold combination is determined based on the corresponding positions of the design flood and design drainage in the two-dimensional index space.

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