A method and system for predicting rainstorm disaster risk

Abstract

The present invention relates to the field of meteorological technology, and discloses a method and system for predicting the risk of rainstorm disasters, the method comprising obtaining meteorological data and environmental parameters of the area to be evaluated; calculating the risk index of disaster-causing factors, including the rainstorm disaster risk index, the disaster-prone environmental impact coefficient, and the daily rainstorm intensity index; obtaining geographical hydrological parameters and ecological environmental parameters, and judging the drainage capacity; calculating the sensitivity index of the disaster-prone environment, and evaluating the exposure and vulnerability index of the disaster-prone body; calculating the comprehensive disaster risk value in combination with the risk index of the disaster-causing factors, the drainage capacity, the exposure and vulnerability index of the disaster-prone body; and predicting the risk level of rainstorm disasters based on the set threshold classification. The present invention has a clear structure and can adapt to the risk assessment needs of rainstorm disasters in different regions and of different scales; through the set threshold classification, different risk levels can be intuitively divided, providing a clear reference basis for decision makers, and helping to formulate corresponding disaster prevention and mitigation measures.

Description

Technical Field

[0001] The present invention relates to the field of meteorological technology, and in particular to a method and system for predicting rainstorm disaster risk. Background Art

[0002] With the intensification of global climate change, extreme weather events such as rainstorms have occurred frequently, posing a serious threat to people's production and life. In order to effectively deal with rainstorm disasters, it is particularly important to timely and accurately estimate the risk of rainstorm disasters. However, traditional rainstorm disaster risk estimation methods are often limited by the statistical analysis of historical data and the limitations of empirical models. These methods have obvious deficiencies in prediction accuracy and timeliness. Especially in the face of complex and changeable weather systems, traditional methods often find it difficult to capture the real-time dynamic changes of rainstorm disasters, resulting in a large deviation between the estimated results and the actual situation.

[0003] Therefore, how to develop a more accurate and efficient method and system for predicting rainstorm disaster risks has become an urgent problem to be solved in the current field of meteorological technology. Summary of the invention

[0004] In view of this, the present invention proposes a rainstorm disaster risk prediction method and system, aiming to improve the accuracy and timeliness of rainstorm disaster risk prediction.

[0005] The present invention proposes a method for predicting rainstorm disaster risk, comprising:

[0006] Acquire meteorological data and environmental parameters of the area to be assessed, and calculate the disaster risk index of the area to be assessed, wherein the disaster risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index;

[0007] Acquiring geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and determining the drainage capacity of the area to be assessed based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed;

[0008] Calculate the sensitivity index of the disaster-prone environment based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and assess the exposure and vulnerability index of the disaster-prone body through the sensitivity index;

[0009] The comprehensive disaster risk value is calculated by combining the hazard index of the disaster-causing factors, drainage capacity, exposure degree of the disaster-bearing body and vulnerability index, and the risk level of the rainstorm disaster is predicted based on the set threshold classification.

[0010] Preferably, the meteorological data and environmental parameters of the area to be evaluated include actual rainfall in the previous 24 hours, 3-hour maximum rainfall intensity forecast, daily rainfall forecast, terrain slope, vegetation coverage and soil permeability.

[0011] Preferably, meteorological data and environmental parameters of the area to be evaluated are obtained, and the disaster-causing factor risk index of the area to be evaluated is calculated, wherein the disaster-causing factor risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index, including:

[0012] The rainstorm disaster risk index, disaster-prone environmental impact coefficient, and daily rainstorm intensity index are calculated according to the following formula:

[0013] H = A1 × S1 + A2 × S2 + A3 × S3;

[0014] Ie=C1×T+C2×S+C3×P;

[0015] IR = B1 × S1 + B2 × S2 + B3 × S3;

[0016] Among them, H represents the rainstorm disaster hazard index; S1 represents the actual rainfall in the previous 24 hours; S2 represents the 3-hour maximum rainfall forecast; S3 represents the daily rainfall forecast; A1, A2, A3 represent the corresponding weights; e represents the disaster-prone environmental impact coefficient; T represents the terrain slope; S represents the vegetation coverage; P represents the soil permeability; C1, C2, C3 represent the coefficients; IR represents the daily rainstorm intensity index; B1, B2, B3 represent the coefficients;

[0017] The disaster-causing factor hazard index is calculated based on the rainstorm disaster hazard index, the disaster-prone environmental impact coefficient, and the daily rainstorm intensity index: disaster-causing factor hazard index=H×Ie×IR.

[0018] Preferably, the geographical and hydrological parameters of the area to be evaluated include terrain slope, soil permeability, soil type and surface water flow; the ecological and environmental parameters of the area to be evaluated include vegetation coverage and infrastructure impact.

[0019] Preferably, judging the drainage capacity of the area to be evaluated based on the geographical hydrological parameters and ecological environmental parameters of the area to be evaluated includes:

[0020] Calculate the drainage capacity according to the following formula:

[0021] ;

[0022] Where Dc represents the drainage capacity of the drainage system; GH represents the terrain slope; P represents the soil permeability; Q represents the soil type; E represents the surface water flow; S represents the vegetation coverage; IVI represents the infrastructure impact; f(Q) represents the function of soil type, which is defined as a numerical mapping;

[0023] The infrastructure impact is obtained by the following calculation formula:

[0024] ;

[0025] Among them, Dc represents the drainage capacity of the drainage system; Da represents the actual drainage capacity; Cc represents the patency of the river channel; Br represents the flood resistance level of the building; Rt represents the critical demand for the bearing capacity of roads and bridges; Rc represents the bearing capacity of roads and bridges; Ud represents the interruption time of water supply and power supply; Um represents the maximum interruption time of water supply and power supply; Ea represents the patency of the emergency rescue channel; Hh represents the historical disaster record.

[0026] Preferably, the calculation of the sensitivity index of the disaster-prone environment according to the geographical hydrological parameters and ecological environmental parameters of the area to be assessed includes:

[0027] ;

[0028] Among them, Se represents the disaster-prone environment sensitivity index; GH represents the terrain slope; IVI represents the infrastructure impact index; S represents the vegetation coverage; P represents the soil permeability; Q represents the soil type sensitivity coefficient; γ1, γ2, γ3, and γ4 represent the weight coefficients.

[0029] Preferably, when evaluating the exposure and vulnerability index of the disaster-prone body by the sensitivity index, it includes:

[0030] ;

[0031] Among them, Ve represents the exposure and vulnerability index of the disaster-prone body; Dp represents the population density; Ec represents the concentration of economic activities; Br represents the building disaster resistance index; Hh represents the historical disaster record coefficient; Ut represents the water supply and power supply interruption risk index; δ1, δ2, δ3, and δ4 represent the weight coefficients of different factors.

[0032] Preferably, the comprehensive disaster risk value is calculated by combining the hazard index of the disaster-causing factor, the drainage capacity, the exposure degree of the disaster-bearing body and the vulnerability index, and the risk level of the rainstorm disaster is predicted based on the set threshold classification, including:

[0033] ;

[0034] Among them, R represents the comprehensive disaster risk value; H represents the hazard index of disaster-causing factors; Se represents the disaster-prone environment sensitivity index; Dc represents the drainage capacity; Ve represents the exposure and vulnerability index of the disaster-prone body; Ie represents the disaster-prone environment impact coefficient; IR represents the daily rainstorm intensity index; λ1 and λ2 represent weight coefficients.

[0035] Preferably, based on the set threshold classification, the risk level of rainstorm disaster is predicted, including:

[0036] Grade V: R≤50%;

[0037] Level IV: 50% <R≤70%;

[0038] Grade III: 70% <R≤85%;

[0039] Grade II: 85% <R≤95%;

[0040] Level I: 95% <R;

[0041] Among them, Level V <Level IV <Level III <Level II <Level I.

[0042] The present invention also proposes a rainstorm disaster risk prediction system, which is used to implement the above-mentioned rainstorm disaster risk prediction method. The rainstorm disaster risk prediction system includes a data acquisition module, a data processing module, a risk assessment module and an early warning release module;

[0043] The data acquisition module is configured to collect meteorological data, environmental parameters, geographical and hydrological parameters, and ecological and environmental parameters of the area to be evaluated;

[0044] The data processing module pre-processes and analyzes the collected data to meet the calculation requirements of the risk assessment module;

[0045] The risk assessment module calculates the hazard index of the disaster-causing factor, the drainage capacity, the exposure degree and the vulnerability index of the disaster-bearing body according to the processed data, and calculates the comprehensive disaster risk value in combination with these indexes;

[0046] The warning release module predicts the risk level of rainstorm disasters based on the comprehensive disaster risk value and the set threshold classification.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The accuracy of the rainstorm disaster risk assessment is improved. By comprehensively considering the hazard index of the disaster-causing factor, drainage capacity, exposure and vulnerability index of the disaster-bearing body, the disaster risk can be assessed more comprehensively. The dynamic risk assessment based on real-time data is realized. The data acquisition module can collect meteorological data and environmental parameters in real time, making the risk assessment more timely and dynamic. Through the early warning release module, the rainstorm disaster risk warning can be quickly issued to relevant departments and the public, improving the preparation time and efficiency for responding to disasters. The present invention has a clear structure and can adapt to the risk assessment needs of rainstorm disasters in different regions and of different scales. Through the set threshold classification, different risk levels can be intuitively divided, providing a clear reference basis for decision makers, which is helpful to formulate corresponding disaster prevention and mitigation measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0050] Figure 1 The present invention is a flow chart of the method for predicting the risk of rainstorm disasters. DETAILED DESCRIPTION

[0051] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0052] See also Figure 1 The present invention proposes a method for predicting rainstorm disaster risk, comprising:

[0053] Acquire meteorological data and environmental parameters of the area to be assessed, and calculate the disaster risk index of the area to be assessed, wherein the disaster risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index;

[0054] Acquiring geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and determining the drainage capacity of the area to be assessed based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed;

[0055] Calculate the sensitivity index of the disaster-prone environment based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and assess the exposure and vulnerability index of the disaster-prone body through the sensitivity index;

[0056] The comprehensive disaster risk value is calculated by combining the hazard index of the disaster-causing factors, drainage capacity, exposure degree of the disaster-bearing body and vulnerability index, and the risk level of the rainstorm disaster is predicted based on the set threshold classification.

[0057] It can be understood that the present invention proposes a method for predicting the risk of rainstorm disasters, which can effectively assess the potential disaster risk of a specific area under rainstorm conditions. The specific steps include:

[0058] Obtain meteorological data and environmental parameters of the area to be assessed: First, collect meteorological data of the area to be assessed, including but not limited to historical rainfall records, rainfall intensity, rainfall frequency, etc. At the same time, obtain environmental parameters such as topography, soil type, vegetation coverage, etc. These parameters are crucial for assessing the risk of rainstorm disasters.

[0059] Calculate the disaster risk index of the area to be assessed: Based on the collected data, calculate the rainstorm disaster risk index, which reflects the potential harm of rainstorm events. In addition, it is necessary to calculate the disaster-prone environmental impact coefficient, which takes into account the impact of environmental factors on the occurrence of disasters. The daily rainstorm intensity index is also an important parameter for assessing the risk of rainstorm disasters, which measures the intensity of rainfall in a single day.

[0060] Obtain geo-hydrological and ecological environmental parameters: Obtain geo-hydrological parameters of the area to be assessed, such as river distribution, lake location, terrain slope, etc., through the use of geographic information systems (GIS) and other technical means. At the same time, collect ecological environmental parameters, including vegetation type, land use, soil moisture, etc. These parameters are crucial for assessing the drainage capacity of the area and the health of the ecosystem.

[0061] Determine drainage capacity: Evaluate the drainage capacity of the area to be evaluated based on geographical hydrological parameters and ecological environmental parameters. The level of drainage capacity directly affects the possibility of waterlogging and flooding after heavy rain.

[0062] Calculate the sensitivity index of the disaster-prone environment: By analyzing the geographical hydrological parameters and the ecological environmental parameters, the sensitivity index of the disaster-prone environment is calculated. This index reflects the sensitivity of the environment to rainstorm disasters, that is, the vulnerability of the environment under the influence of rainstorms.

[0063] Assess the exposure and vulnerability index of the hazard-prone objects: Combined with the sensitivity index, assess the exposure and vulnerability index of the hazard-prone objects (such as buildings, infrastructure, population, etc.). Exposure refers to the possibility of the hazard-prone object being affected by a disaster, while the vulnerability index reflects the extent of the loss that the hazard-prone object may suffer when a disaster occurs.

[0064] Calculate the comprehensive disaster risk value: Take into account the hazard index of the disaster factor, drainage capacity, exposure and vulnerability index of the disaster-bearing body, and calculate the comprehensive disaster risk value. This value can fully reflect the potential risk level of the area to be assessed under heavy rain conditions.

[0065] Predicting the risk level of rainstorm disasters: Based on the set threshold classification, the comprehensive disaster risk value is compared with the preset risk level standard to predict the risk level of rainstorm disasters. This step helps decision makers take corresponding preventive measures and emergency response strategies to mitigate potential disaster impacts.

[0066] Through the above steps, the rainstorm disaster risk estimation method provided by the present invention can provide a scientific basis for urban planning, disaster management, emergency response, etc., and help improve the society's ability to respond to rainstorm disasters.

[0067] In some embodiments of the present application, the meteorological data and environmental parameters of the area to be evaluated include actual rainfall in the previous 24 hours, 3-hour maximum rainfall intensity forecast, daily rainfall forecast, terrain slope, vegetation coverage and soil permeability.

[0068] It is understandable that, in this embodiment, the meteorological data and environmental parameters of the area to be evaluated include the actual rainfall in the previous 24 hours, the maximum rainfall intensity forecast in 3 hours, the daily rainfall forecast, the terrain slope, the vegetation coverage and the soil permeability. These parameters are crucial for evaluating the flood risk, soil erosion and other environmental problems related to hydrology and meteorology in the area. For example, the actual rainfall in the previous 24 hours can provide direct information about the rainfall that has occurred, while the maximum rainfall intensity forecast in 3 hours helps to predict the extreme rainfall events that may occur in the short term. The daily rainfall forecast provides an expected value for the total rainfall in the next 24 hours, which is crucial for the deployment of flood control measures and the allocation of resources. The terrain slope, the vegetation coverage and the soil permeability provide clues about how the surface responds to rainfall. For example, a steep terrain slope may accelerate the flow of water, while a good vegetation coverage and a high soil permeability help absorb and slow down the flow of water and reduce the risk of floods. By combining these data, the environmental risks of a specific area can be more accurately assessed and corresponding countermeasures can be formulated.

[0069] In some embodiments of the present application, meteorological data and environmental parameters of the area to be evaluated are obtained, and the disaster risk index of the area to be evaluated is calculated, wherein the disaster risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index, including:

[0070] The rainstorm disaster risk index, disaster-prone environmental impact coefficient, and daily rainstorm intensity index are calculated according to the following formula:

[0071] H = A1 × S1 + A2 × S2 + A3 × S3;

[0072] Ie=C1×T+C2×S+C3×P;

[0073] IR = B1 × S1 + B2 × S2 + B3 × S3;

[0074] Among them, H represents the rainstorm disaster hazard index; S1 represents the actual rainfall in the previous 24 hours; S2 represents the 3-hour maximum rainfall forecast; S3 represents the daily rainfall forecast; A1, A2, A3 represent the corresponding weights; e represents the disaster-prone environmental impact coefficient; T represents the terrain slope; S represents the vegetation coverage; P represents the soil permeability; C1, C2, C3 represent the coefficients; IR represents the daily rainstorm intensity index; B1, B2, B3 represent the coefficients;

[0075] The disaster-causing factor hazard index is calculated based on the rainstorm disaster hazard index, the disaster-prone environmental impact coefficient, and the daily rainstorm intensity index: disaster-causing factor hazard index=H×Ie×IR.

[0076] It is understandable that in this embodiment, the meteorological data and environmental parameters of the area to be evaluated are first obtained. These data and parameters include but are not limited to the actual rainfall in the previous 24 hours, the maximum rainfall intensity forecast in the next 3 hours, the daily rainfall forecast, the terrain slope, the vegetation coverage and the soil permeability. This information is crucial for assessing the potential disaster risks in the area.

[0077] Next, the rainstorm disaster hazard index (H), disaster-prone environmental impact coefficient (Ie) and daily rainstorm intensity index (IR) are calculated according to the following formula: Finally, the disaster factor hazard index is obtained by multiplying the rainstorm disaster hazard index (H), disaster-prone environmental impact coefficient (Ie) and daily rainstorm intensity index (IR) calculated above.

[0078] This disaster risk index comprehensively considers the impact of rainfall, environmental factors and rainfall intensity on disaster risk, and provides a quantitative indicator for assessing the potential disaster risk in a region. Through this index, disaster risks in different regions can be compared and ranked, thus providing a scientific basis for disaster prevention and emergency response.

[0079] In some embodiments of the present application, the geographical hydrological parameters of the area to be evaluated include terrain slope, soil permeability, soil type and surface water flow; the ecological environmental parameters of the area to be evaluated include vegetation coverage and infrastructure impact.

[0080] It is to be understood that the geo-hydrological parameters of the assessment area in this embodiment include terrain slope, soil permeability, soil type and surface water flow. Terrain slope refers to the degree of inclination of the surface, which affects the direction and speed of water flow, as well as the possibility of erosion. Soil permeability describes the ability of the soil to allow water to pass through, which is crucial for determining the recharge of surface water and groundwater. Soil type involves the texture, structure and composition of the soil, which together determine the water retention capacity of the soil and the types of plants suitable for planting. Surface water flow involves the direction, velocity and flow of rivers, streams and other water bodies, and this information is crucial for assessing flood risks and water resource management.

[0081] At the same time, the ecological and environmental parameters of the area to be assessed include vegetation coverage and infrastructure impact. Vegetation coverage refers to the percentage of ground covered by vegetation in an area, which reflects the health of the ecosystem and the level of biodiversity. Vegetation not only helps prevent soil erosion, but also provides wildlife habitats and affects climate and hydrological cycles. Infrastructure impacts involve the intervention of human activities in the natural environment, including the potential impact of roads, buildings, farmland and other engineering structures on topography, hydrology and ecosystems. The layout and scale of infrastructure may affect surface water flow, soil erosion and biological habitats, so these factors need to be considered in environmental assessments.

[0082] In some embodiments of the present application, judging the drainage capacity of the area to be evaluated based on the geographical hydrological parameters and ecological environmental parameters of the area to be evaluated includes:

[0083] Calculate the drainage capacity according to the following formula:

[0084] ;

[0085] Where Dc represents the drainage capacity of the drainage system; GH represents the terrain slope; P represents the soil permeability; Q represents the soil type; E represents the surface water flow; S represents the vegetation coverage; IVI represents the infrastructure impact; f(T) represents the function of soil type, which is defined as a numerical mapping;

[0086] The infrastructure impact is obtained by the following calculation formula:

[0087] ;

[0088] Among them, Dc represents the drainage capacity of the drainage system; Da represents the actual drainage capacity; Cc represents the patency of the river channel; Br represents the flood resistance level of the building; Rt represents the critical demand for the bearing capacity of roads and bridges; Rc represents the bearing capacity of roads and bridges; Ud represents the interruption time of water supply and power supply; Um represents the maximum interruption time of water supply and power supply; Ea represents the patency of the emergency rescue channel; Hh represents the historical disaster record.

[0089] It is understandable that this embodiment adopts a comprehensive quantitative method for the drainage capacity assessment process of the area to be assessed, which fully considers the diversity of geo-hydrological parameters and ecological environmental parameters and their impact on drainage capacity. Specifically, we designed a composite calculation formula to quantify drainage capacity (D), which integrates multiple key factors, including terrain slope (GH), soil permeability (P), soil type (T), surface water flow (E), vegetation coverage (S) and infrastructure impact (IVI).

[0090] Among these factors, infrastructure impact (IVI) is a particularly important composite indicator, which is further refined into multiple sub-items to comprehensively reflect the restrictive or promoting role of infrastructure on drainage capacity. Specifically, the calculation of IVI takes into account the drainage capacity (Dc) of the drainage system, the actual drainage capacity (Da), the patency of the river channel (Cc), the flood resistance level of buildings (Br), the comparison between the critical demand for road and bridge bearing capacity (Rt) and the actual bearing capacity (Rc), the comparison between the water and power supply interruption time (Ud) and the maximum allowable interruption time (Um), as well as the patency of emergency rescue channels (Ea) and historical disaster records (Hh) and other factors.

[0091] Through this calculation method, we can not only obtain a numerical value (D) that directly reflects the drainage capacity of the area to be evaluated, but also gain a deep understanding of how various factors act on the drainage system individually or together. This quantitative evaluation method not only improves the accuracy and comprehensiveness of the evaluation, but also enhances the scientific nature and operability of decision-making.

[0092] In some embodiments of the present application, when calculating the sensitivity index of the disaster-prone environment according to the geographical hydrological parameters and ecological environmental parameters of the area to be evaluated, it includes:

[0093] ;

[0094] Among them, Se represents the disaster-prone environment sensitivity index; GH represents the terrain slope; IVI represents the infrastructure impact index; S represents the vegetation coverage; P represents the soil permeability; Q represents the soil type sensitivity coefficient; γ1, γ2, γ3, and γ4 represent the weight coefficients.

[0095] It can be understood that, when calculating the sensitivity index of the disaster-prone environment according to the geographical hydrological parameters and ecological environmental parameters of the area to be evaluated, this embodiment includes the following steps:

[0096] Collect data on geohydrological parameters and ecological environmental parameters of the area to be assessed, including but not limited to terrain slope, infrastructure impact index, vegetation coverage, soil permeability and soil type sensitivity coefficient.

[0097] Based on the collected data, the value of terrain slope (GH) is calculated. Terrain slope is an important factor affecting the sensitivity of disaster-prone environments. Generally, the greater the slope, the higher the environmental sensitivity.

[0098] The Infrastructure Impact Index (IVI) is calculated to reflect the potential impact of infrastructure construction on the disaster-prone environment. The layout, scale and type of infrastructure will affect environmental sensitivity.

[0099] Assess vegetation cover (S). Vegetation cover is an indicator to measure the condition of surface vegetation. High vegetation cover usually helps to reduce environmental sensitivity.

[0100] Measure soil permeability (P). Soil permeability determines the infiltration capacity of surface water. Soil with low permeability is prone to accumulation of surface water, increasing the sensitivity of the disaster-prone environment.

[0101] Determine the soil type sensitivity coefficient (T). Different types of soil have different sensitivities to environmental changes, and the corresponding sensitivity coefficient needs to be determined based on the soil type.

[0102] Weight coefficients (γ1, γ2, γ3, γ4) are applied, which are used to adjust the relative importance of each parameter in calculating the disaster-prone environmental sensitivity index (Se).

[0103] Finally, the disaster-prone environmental sensitivity index (Se) was calculated according to the following formula.

[0104] Through the above steps, an index value that comprehensively reflects the disaster-prone environmental sensitivity of the area to be assessed can be obtained.

[0105] In some embodiments of the present application, when evaluating the exposure and vulnerability index of the hazard-prone body by the sensitivity index, it includes:

[0106] ;

[0107] Among them, Ve represents the exposure and vulnerability index of the disaster-prone body; Dp represents the population density; Ec represents the concentration of economic activities; Br represents the building disaster resistance index; Hh represents the historical disaster record coefficient; Ut represents the water supply and power supply interruption risk index; δ1, δ2, δ3, and δ4 represent the weight coefficients of different factors.

[0108] It can be understood that, when evaluating the exposure and vulnerability index of the disaster-prone body through the sensitivity index in this embodiment, the following steps are included:

[0109] Determine the exposure and vulnerability index (Ve) of the hazard-prone body, which is an indicator to measure the sensitivity and potential losses of a specific area or hazard-prone body when facing natural disasters.

[0110] Collect and analyze population density (Dp) data, which reflects the number of people living in a specific area. The higher the population density, the greater the exposure of the hazard-prone body.

[0111] Assess the concentration of economic activities (Ec), which reflects the degree of concentration of economic activities in a specific area. The more concentrated the economic activities are, the greater the economic losses that may be caused when a disaster occurs.

[0112] Consider the Building Disaster Resistance Index (Br), which assesses a building's ability to resist disasters when a disaster occurs based on factors such as its structure, design and materials.

[0113] Analyze the historical disaster record coefficient (Hh), which is based on the historical records of disaster events and evaluates the frequency and intensity of disasters suffered by specific areas or disaster-prone bodies in history.

[0114] Assess the water and power supply interruption risk index (Ut), which takes into account the risk level of water and power supply interruption that may occur when a disaster occurs.

[0115] Determine the weight coefficients of different factors (δ1, δ2, δ3, δ4), which are used to adjust the relative importance of each factor in calculating the exposure and vulnerability index of the hazard-prone body.

[0116] Finally, the exposure and vulnerability index (Ve) of the hazard-prone body are calculated.

[0117] Through such calculations, a comprehensive exposure and vulnerability index of hazard-prone objects can be obtained, thus providing a scientific basis for disaster risk assessment and management.

[0118] In some embodiments of the present application, the comprehensive disaster risk value is calculated by combining the hazard index of the hazard factor, the drainage capacity, the exposure degree of the hazard-bearing body and the vulnerability index, and the risk level of the rainstorm disaster is predicted based on the set threshold classification, including:

[0119] ;

[0120] Among them, R represents the comprehensive disaster risk value; H represents the hazard index of disaster-causing factors; Se represents the disaster-prone environment sensitivity index; Dc represents the drainage capacity; Ve represents the exposure and vulnerability index of the disaster-prone body; Ie represents the disaster-prone environment impact coefficient; IR represents the daily rainstorm intensity index; λ1 and λ2 represent weight coefficients.

[0121] It can be understood that this embodiment combines the hazard index of the disaster factor, the drainage capacity, the exposure degree of the disaster-bearing body and the vulnerability index to calculate the comprehensive disaster risk value, and predicts the risk level of the rainstorm disaster based on the set threshold classification, including:

[0122] Determine the disaster risk index (H), which reflects the potential danger level of rainstorm events, including factors such as rainfall amount, rainfall intensity and rainfall duration.

[0123] Assessing drainage capacity (Dc), the index measures the efficiency of the area's drainage system, including drainage pipe capacity, drainage speed, and maintenance status of the drainage system.

[0124] Analyze the exposure and vulnerability index (Ve) of disaster-prone objects. This index takes into account the degree of exposure of population, property, infrastructure, etc. to rainstorm disasters and their vulnerability, such as the water resistance of buildings and the degree of perfection of flood control measures.

[0125] Consider the disaster-prone environmental sensitivity index (Se), which reflects the sensitivity of a specific area to rainstorm disasters, including factors such as topography, soil type, and vegetation cover.

[0126] The disaster-prone environmental impact coefficient (Ie) is introduced, which is used to adjust the comprehensive disaster risk value to reflect the impact of specific environmental factors on disaster risk.

[0127] Combined with the daily rainstorm intensity index (IR), which describes the intensity of rainfall in a specific period of time, it is an important parameter for assessing the risk of rainstorm disasters.

[0128] Weight coefficients (λ1, λ2) are applied, which are used to adjust the relative importance of the above indices in the calculation of the comprehensive disaster risk value.

[0129] Calculation of comprehensive disaster risk value (R).

[0130] Through the above steps and calculations, a comprehensive disaster risk value can be obtained, which combines multiple factors and can more accurately predict and grade the risk level of rainstorm disasters. According to the calculated comprehensive disaster risk value, different thresholds can be set to divide the risk level into low, medium, high or higher, so as to take corresponding prevention and response measures.

[0131] In some embodiments of the present application, based on the set threshold classification, the risk level of rainstorm disaster is predicted, including:

[0132] Grade V: R≤50%;

[0133] Level IV: 50% <R≤70%;

[0134] Grade III: 70% <R≤85%;

[0135] Grade II: 85% <R≤95%;

[0136] Level I: 95% <R;

[0137] Among them, Level V <Level IV <Level III <Level II <Level I.

[0138] It can be understood that this embodiment includes the following five levels when predicting the risk level of rainstorm disasters based on the set threshold level:

[0139] Level V: When the predicted rainstorm disaster risk probability R is less than or equal to 50%, it means that the possibility of rainstorm disaster is low and the risk level is Level V.

[0140] Level IV: When the predicted rainstorm disaster risk probability R is greater than 50% and less than or equal to 70%, it means that the possibility of rainstorm disasters has increased and the risk level is Level IV.

[0141] Level III: When the predicted rainstorm disaster risk probability R is greater than 70% and less than or equal to 85%, it means that the possibility of rainstorm disasters is further increased and the risk level is Level III.

[0142] Level II: When the predicted rainstorm disaster risk probability R is greater than 85% and less than or equal to 95%, it means that the possibility of rainstorm disaster is very high and the risk level is Level II.

[0143] Level I: When the predicted rainstorm disaster risk probability R is greater than 95%, it means that the possibility of rainstorm disaster is extremely high and the risk level is Level I.

[0144] The above five levels are arranged from low to high according to the risk probability, that is, Level V < Level IV < Level III < Level II < Level I, reflecting the gradual increase from low risk to high risk. Such a classification helps relevant departments and the public to take corresponding preventive measures to reduce the possible impact of rainstorm disasters.

[0145] The present invention also proposes a rainstorm disaster risk prediction system, which is used to implement the above-mentioned rainstorm disaster risk prediction method. The rainstorm disaster risk prediction system includes a data acquisition module, a data processing module, a risk assessment module and an early warning release module;

[0146] The data acquisition module is configured to collect meteorological data, environmental parameters, geographical and hydrological parameters, and ecological and environmental parameters of the area to be evaluated;

[0147] The data processing module pre-processes and analyzes the collected data to meet the calculation requirements of the risk assessment module;

[0148] The risk assessment module calculates the hazard index of the disaster-causing factor, the drainage capacity, the exposure degree and the vulnerability index of the disaster-bearing body according to the processed data, and calculates the comprehensive disaster risk value in combination with these indexes;

[0149] The warning release module predicts the risk level of rainstorm disasters based on the comprehensive disaster risk value and the set threshold classification.

[0150] It is understandable that this embodiment relates to a rainstorm disaster risk prediction system, which can effectively implement a rainstorm disaster risk prediction method. The rainstorm disaster risk prediction system mainly consists of four modules: a data acquisition module, a data processing module, a risk assessment module, and a warning release module.

[0151] The data acquisition module is responsible for collecting various key data in the area to be assessed. These data include meteorological data, such as precipitation, wind speed, temperature, etc.; environmental parameters, such as soil moisture, vegetation coverage, etc.; geographical and hydrological parameters, such as topography, distribution of rivers and lakes, drainage system conditions, etc.; and ecological and environmental parameters, such as biodiversity, land use type, etc. These data provide the necessary basic information for risk assessment.

[0152] The data processing module preprocesses and analyzes the data collected by the data acquisition module. Preprocessing may include data cleaning, format conversion, missing value processing, etc. to ensure data quality. Analysis involves data statistics, trend prediction, anomaly detection, etc. to extract information useful for risk assessment and convert the data into the format required by the risk assessment module.

[0153] The risk assessment module is the core of the system, which uses the data provided by the data processing module to calculate multiple key indices. These indices include the hazard risk index of hazard factors, which reflects the potential destructive power of rainstorm events; the drainage capacity index, which evaluates the ability of the drainage system in the region to cope with rainstorms; the exposure index of the hazard-bearing body, which describes the degree of exposure of the population, property, etc. to rainstorm risks; and the vulnerability index, which measures the disaster resistance of socio-economic conditions and infrastructure. By combining these indices, the risk assessment module is able to calculate a comprehensive disaster risk value, which reflects the possibility of rainstorm disasters and the possible losses under specific conditions.

[0154] The warning release module classifies the disaster risk value and the preset threshold value to predict the risk level of rainstorm disasters. If the calculated risk value exceeds the set threshold, the warning release module will be activated to release the corresponding warning information to relevant departments and the public. The warning information may include the risk level, the area that may be affected, the recommended preventive measures, etc., so that timely response measures can be taken to reduce the possible impact of rainstorm disasters.

[0155] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting rainstorm disaster risk, characterized in that: include: Acquire meteorological data and environmental parameters of the area to be assessed, and calculate the disaster risk index of the area to be assessed, wherein the disaster risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index; Acquiring geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and determining the drainage capacity of the area to be assessed based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed; Calculate the sensitivity index of the disaster-prone environment based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed, and assess the exposure and vulnerability index of the disaster-prone body through the sensitivity index; The comprehensive disaster risk value is calculated by combining the hazard index of the disaster-causing factor, drainage capacity, exposure degree of the disaster-bearing body and vulnerability index, and the risk level of the rainstorm disaster is predicted based on the set threshold classification; The geo-hydrological parameters of the area to be assessed include terrain slope, soil permeability, soil type and surface water flow; the ecological and environmental parameters of the area to be assessed include vegetation coverage and infrastructure impact; When judging the drainage capacity of the area to be assessed based on the geographical hydrological parameters and ecological environmental parameters of the area to be assessed, it includes: Calculate the drainage capacity according to the following formula: Dc=GH·P·S·f(Q)·IVI·E; Where Dc represents drainage capacity; GH represents terrain slope; P represents soil permeability; Q represents soil type; E represents surface water flow; S represents vegetation coverage; IVI represents infrastructure impact; f(Q) represents a function of soil type, defined as a numerical mapping; The infrastructure impact is obtained by the following calculation formula: Among them, Dc represents the drainage capacity of the drainage system; Da represents the actual drainage capacity; Cc represents the patency of the river channel; Br represents the flood resistance level of the building; Rt represents the critical demand for the carrying capacity of roads and bridges; Rc represents the carrying capacity of roads and bridges; Ud represents the interruption time of water supply and power supply; Um represents the maximum interruption time of water supply and power supply; Ea represents the patency of the emergency rescue channel; Hh represents the historical disaster record; The meteorological data and environmental parameters of the area to be evaluated include the actual rainfall in the previous 24 hours, the maximum rainfall intensity forecast in 3 hours, the daily rainfall forecast, the terrain slope, the vegetation coverage and the soil permeability; Obtaining meteorological data and environmental parameters of the area to be assessed, and calculating the disaster risk index of the area to be assessed, wherein the disaster risk index includes a rainstorm disaster risk index, a disaster-prone environmental impact coefficient, and a daily rainstorm intensity index, including: The rainstorm disaster risk index, disaster-prone environmental impact coefficient, and daily rainstorm intensity index are calculated according to the following formula: H = A1 × S1 + A2 × S2 + A3 × S3; Ie=C1×T+C2×S+C3×P; IR = B1 × S1 + B2 × S2 + B3 × S3; Among them, H represents the rainstorm disaster hazard index; S1 represents the actual rainfall in the previous 24 hours; S2 represents the 3-hour maximum rainfall forecast; S3 represents the daily rainfall forecast; A1, A2, A3 represent the corresponding weights; le represents the disaster-prone environmental impact coefficient; T represents the terrain slope; S represents the vegetation coverage; P represents the soil permeability; C1, C2, C3 represent the coefficients; IR represents the daily rainstorm intensity index; B1, B2, B3 represent the coefficients; The disaster-causing factor risk index is calculated according to the rainstorm disaster risk index, the disaster-prone environmental impact coefficient, and the daily rainstorm intensity index: disaster-causing factor risk index = H × Ie × IR; According to the geographical hydrological parameters and ecological environmental parameters of the area to be assessed, the sensitivity index of the disaster-prone environment is calculated, including: Among them, Se represents the disaster-prone environment sensitivity index; GH represents the terrain slope; IVI represents the infrastructure impact index; S represents the vegetation coverage; P represents the soil permeability; T represents the soil type sensitivity coefficient; γ1, γ2, γ3, and γ4 represent the weight coefficients; When evaluating the exposure and vulnerability index of the hazard-prone body through the sensitivity index, it includes: Among them, Ve represents the exposure and vulnerability index of the disaster-prone body; Dp represents the population density; Ec represents the concentration of economic activities; Br represents the building disaster resistance index; Hh represents the historical disaster record; Ut represents the water supply and power supply interruption risk index; δ1, δ2, δ3, δ4 represent the weight coefficients of different factors; The comprehensive disaster risk value is calculated by combining the hazard index of the hazard factor, drainage capacity, exposure degree of the hazard-bearing body and vulnerability index. Based on the set threshold classification, the risk level of the rainstorm disaster is predicted, including: Among them, R represents the comprehensive disaster risk value; H represents the hazard index of disaster-causing factors; Se represents the disaster-prone environment sensitivity index; Dc represents the drainage capacity; Ve represents the exposure and vulnerability index of the disaster-prone body; Ie represents the disaster-prone environment impact coefficient; IR represents the daily rainstorm intensity index; λ1 and λ2 represent weight coefficients.

2. The method for predicting rainstorm disaster risk according to claim 1, characterized in that: Based on the set threshold classification, the risk level of rainstorm disasters is predicted, including: Grade V: R ≤ 50%; Level IV: 50% <R≤70%; Grade III: 70% <R≤85%; Level II: 85% <R≤95%; Level I: 95% <R; Among them, Level V <Level IV <Level III <Level II <Level I.

3. A rainstorm disaster risk prediction system, used to implement the rainstorm disaster risk prediction method according to any one of claims 1-2, characterized in that: The rainstorm disaster risk prediction system includes a data acquisition module, a data processing module, a risk assessment module and an early warning release module; The data acquisition module is configured to collect meteorological data, environmental parameters, geographical and hydrological parameters, and ecological and environmental parameters of the area to be evaluated; The data processing module pre-processes and analyzes the collected data to meet the calculation requirements of the risk assessment module; The risk assessment module calculates the hazard index of the disaster-causing factor, the drainage capacity, the exposure degree and the vulnerability index of the disaster-bearing body according to the processed data, and calculates the comprehensive disaster risk value in combination with these indexes; The warning release module predicts the risk level of rainstorm disasters based on the comprehensive disaster risk value and the set threshold classification.

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