Flood disaster flooding prediction and graded early warning method considering flood peak process

Abstract

The invention relates to the technical field of flood disaster early warning, in particular to a flood disaster flooding prediction and graded early warning method considering a flood peak process, and the method comprises the following steps: constructing the spatial data of an easy-to-flood region in a flood disaster; predicting future rainfall data; rainfall runoff simulation is carried out on each simulation calculation unit, and the river channel confluence runoff volume in each simulation calculation unit is analyzed; generating river boundary conditions and urban boundary conditions; constructing a flood routing model, and respectively predicting the propagation process of flood in the river region and the city region in each simulation calculation unit through a river shallow water equation and a city shallow water equation based on river boundary conditions and city boundary conditions; and according to a prediction result of the flood routing model, evaluating a risk level of a flood disaster, and generating a corresponding emergency plan. By adopting the scheme, accurate flood disaster prediction can be realized, the spreading process of flood in a city can be accurately described, and the risk level of the flood disaster can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of flood disaster early warning, and in particular to a flood disaster inundation prediction and graded early warning method taking into account a flood peak process. Background Art

[0002] In today's society, floods have become one of the major natural disasters that affect human life and economic development. With climate change and the acceleration of urbanization, the frequency and intensity of floods have increased, posing a serious threat to people's lives and property safety, especially for mountainous cities. The steep terrain, complex water network and dense population distribution make the flood evolution process more complex and changeable. Therefore, how to accurately predict the occurrence, development and impact range of floods, as well as how to effectively warn and respond, has become an urgent problem to be solved in practical applications.

[0003] Traditional flood disaster prediction methods mainly rely on historical experience and simple statistical analysis, which often fail to accurately reflect the complex flood evolution process and the combined effects of multiple influencing factors. Although the development of remote sensing technology, geographic information system (GIS) and hydrological models has provided new tools and methods for flood simulation, most flood simulation methods still use simplified mathematical models and empirical formulas to estimate the generation and propagation process of floods. These methods are often not accurate enough when dealing with complex terrain and urban areas. Specifically, the treatment of complex terrain and urban areas is often oversimplified, making it difficult to accurately describe the propagation characteristics of floods in these areas; secondly, existing methods often ignore some key factors in the flood evolution process, which affects the accuracy of the prediction results. Therefore, it is urgent to provide a flood disaster inundation prediction and graded warning method that takes into account the flood peak process, which can accurately describe the spread of floods in cities, improve the accuracy of flood disaster prediction, and accurately assess the risk level of inundation disasters, generate corresponding emergency plans, and improve the speed of emergency response. Summary of the invention

[0004] The present invention provides a flood disaster inundation prediction and graded early warning method taking into account the flood peak process, which can accurately depict the spread of floods in cities, improve the accuracy of flood disaster prediction, and thus accurately assess the risk level of inundation disasters, generate corresponding emergency plans, and improve emergency response speed.

[0005] In order to achieve the above objectives, this application provides the following technical solutions:

[0006] A flood disaster inundation prediction and graded early warning method considering the flood peak process includes the following contents:

[0007] Obtaining environmental data of the target area, including historical remote sensing images, measured waterlogging data, historical meteorological data, and watershed distribution characteristics;

[0008] Based on the historical remote sensing images of the target area and the measured data of waterlogging, the spatial data of flood-prone areas are constructed;

[0009] Preprocess the historical meteorological data and predict the future precipitation data of the target area based on the preprocessed historical meteorological data;

[0010] According to the characteristics of watershed distribution, the watershed in the target area is divided into several simulation calculation units; combined with the attribute characteristics of each simulation calculation unit and the future precipitation data of the target area, rainfall runoff simulation is performed on each simulation calculation unit, and the river runoff in each simulation calculation unit is analyzed;

[0011] Analyze the upstream water volume, downstream regulation and storage conditions, and mountain river terrain of each simulation unit, and convert them into river boundary conditions; analyze the building parameters and urban drainage system data in each simulation unit, and convert them into urban boundary conditions;

[0012] A flood evolution model is constructed, and based on the river boundary conditions, the river shallow water equation is used to predict the propagation process of floods in the river area within each simulation calculation unit; the flood evolution model is also used to predict the propagation process of floods in the urban area within each simulation calculation unit based on the city boundary conditions through the city shallow water equation.

[0013] Furthermore, the river boundary conditions include river flow conditions, water storage conditions and flow velocity conditions;

[0014] The river flow conditions are:

[0015] Q 下游 =Q 上游 +Q 山区流域

[0016] In the formula, Q 下游 Q is the flow generated by the downstream regulation of the simulation calculation unit; 上游 is the flow from the upstream of the simulation computing unit; Q 山区流域 To simulate the flow rate within the calculation unit;

[0017] The water storage conditions are:

[0018] V t+1 =V t +Q in ×Δt-Q out ×Δt

[0019] Where V t+1is the reservoir water storage capacity at the next time step, V t is the reservoir water storage capacity at the current time step, Q in is the flow into the reservoir, Q out is the flow out of the reservoir, Δt is the time step;

[0020] The flow rate conditions are:

[0021]

[0022] Where v is the lateral velocity of the water flow in the river, n s is the Manning roughness coefficient, R s is the hydraulic radius and S is the slope of the riverbed.

[0023] Furthermore, the shallow water equation of the river channel is:

[0024]

[0025] In the formula, It represents the rate of change of the amount of water passing through a fixed point per unit time in the x direction; It represents the rate of change of the amount of water passing through a fixed point per unit time in the y direction; represents the horizontal momentum hu in the x direction 2 With potential energy The rate of change of the sum of with spatial position; represents the horizontal momentum hu in the y direction 2 With potential energy The rate of change of the sum of with spatial position; It represents the rate of change of horizontal momentum in the y direction with spatial position; It represents the rate of change of horizontal momentum in the x direction with spatial position; represents the gravity effect caused by the change of riverbed elevation z in the x direction; represents the gravity effect caused by the change of riverbed elevation z in the y direction; represents the resistance term generated by riverbed friction in the x direction; represents the resistance term generated by riverbed friction in the y direction; represents the rate of change of water depth h with time t; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the x direction; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the y direction.

[0026] Furthermore, the city boundary conditions include friction conditions and drainage system flow conditions;

[0027] The friction conditions are:

[0028] F b =-C b ·ρ·A·|u|·u

[0029] In the formula, F b is the resistance term between water flow and buildings, C b is the drag coefficient of the building, ρ is the density of the water flow, A is the vertical projection area of ​​the building, and u is the velocity vector of the water flow;

[0030] The flow conditions of the drainage system are:

[0031] Q d =k d ·h

[0032] In the formula, Q d is the flow through the urban drainage system, k d is the conductivity coefficient of water flow, and h is the water depth.

[0033] Furthermore, the urban shallow water equation is:

[0034]

[0035] In the formula, F x is the component of the resistance caused by the building in the x direction; F y is the component of the drag caused by the building in the y direction.

[0036] Furthermore, the rainfall runoff simulation includes rainfall runoff simulation, slope runoff simulation and river confluence simulation;

[0037] The rainfall runoff simulation is used to analyze the instantaneous infiltration rate of water. The calculation formula of the instantaneous infiltration rate is as follows:

[0038]

[0039] In the formula, F is the instantaneous infiltration rate, Δh represents the change in soil moisture content, Δt represents the time interval, and K s is the saturated hydraulic conductivity of the soil, t is the duration of rainfall, h s is the saturated water head of the soil;

[0040] The slope runoff simulation is used to analyze the slope runoff volume. The calculation formula of the slope runoff volume is as follows:

[0041]

[0042] In the formula, Q slope is the slope runoff, R is the effective rainfall, I a is the initial loss, K is the soil permeability coefficient;

[0043] The river confluence simulation is used to analyze the river confluence runoff. The calculation formula of the river confluence runoff is as follows:

[0044]

[0045] Where Q(t) is the runoff of the river at time t', k i is the weight coefficient of the i-th time step, Δt′ is the time step, and R(t′-iΔt′) represents the surface runoff in the i-th time step.

[0046] Furthermore, the preprocessing includes removing outliers, filling missing values ​​and normalization; the data point values ​​of the historical meteorological data after normalization are:

[0047]

[0048] In the formula, x normalized is the normalized data point value, x is a data point in the original data set, min(x) is the minimum value in the data set, and max(x) is the maximum value in the data set.

[0049] Further, the environmental data also includes digital elevation model data;

[0050] Constructing spatial data of flood-prone areas includes:

[0051] Analyze the flood inundation scope of historical flood disaster areas based on historical remote sensing images and measured waterlogging data;

[0052] Based on the flood inundation range of historical flood disaster areas, the flood-prone areas are analyzed and spatial data of flood-prone areas are constructed.

[0053] Furthermore, the method also includes the following contents: evaluating the risk level of flooding disasters according to the prediction results of the flood evolution model, and generating corresponding emergency plans.

[0054] Furthermore, the attribute characteristics include one or more of mountain terrain characteristics, soil characteristics, land use characteristics, slope characteristics and slope aspect characteristics.

[0055] The principles and advantages of the present invention are:

[0056] 1. Based on the historical remote sensing images and measured data of waterlogging in the target area, spatial data of flood-prone areas are constructed, which is conducive to identifying potential flood risk areas and providing targeted disaster prevention and mitigation information for relevant emergency management departments.

[0057] 2. Through dynamic preprocessing and prediction of meteorological data, combined with rainfall runoff simulation, it is possible to dynamically simulate impending flood events, thereby achieving real-time early warning, providing a valuable time window for emergency evacuation, deployment of rescue materials and the activation of emergency plans.

[0058] 3. Taking into account various boundary conditions such as river flow conditions, water storage conditions, flow velocity conditions, friction conditions and drainage system flow conditions, it can more accurately predict the propagation process of floods in river areas and urban areas, making flood simulation more in line with actual complex situations and ensuring the applicability and reliability of the model, especially in complex terrains such as urban areas and mountainous basins.

[0059] 4. Accurate flood forecasting and risk assessment help optimize resource allocation, ensure that limited resources such as manpower, materials and financial resources are reasonably allocated to where they are most needed, and help improve the cost-effectiveness of disaster prevention and mitigation work. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 The present invention is a flow chart of an embodiment of a flood disaster inundation prediction and graded early warning method taking into account the flood peak process. DETAILED DESCRIPTION

[0061] The following is further described in detail through specific implementation methods:

[0062] Embodiment 1:

[0063] Embodiment 1 is basically as attached Figure 1 As shown:

[0064] A flood disaster inundation prediction and graded warning method considering the flood peak process, mainly through the construction of spatial data of flood-prone areas, prediction of future precipitation data, simulation of rainfall runoff, simulation of river flood evolution, simulation of urban inundation process, proposes graded warning of inundation disasters and generates emergency response strategies, such as Figure 1 As shown, the specific steps include:

[0065] S100, obtaining environmental data of a target area, wherein the environmental data includes historical remote sensing images, measured waterlogging data, historical meteorological data, watershed distribution characteristics, and digital elevation model data.

[0066] S200, based on the historical remote sensing images of the target area and the measured data of waterlogging, constructs the spatial data of flood-prone areas; S200 includes:

[0067] S201, analyzing the flood inundation range of historical flood disaster areas based on historical remote sensing images and measured data on urban waterlogging; in this embodiment, the measured data on urban waterlogging includes waterlogging area and waterlogging depth. If the waterlogging area and waterlogging depth of a waterlogging area both exceed corresponding thresholds, the waterlogging area is determined to be a flood inundation area; based on the flood inundation area, analyzing the flood inundation range of historical flood disaster areas.

[0068] S202: Analyze flood-prone areas according to the flood inundation range of historical flood disaster areas, and construct spatial data of flood-prone areas. Specifically, analyze flood-prone areas according to the number of floods in each flood inundation area within the flood inundation range, and construct spatial data of flood-prone areas by combining the latest high-resolution DEM data and drone photogrammetry technology.

[0069] S300, preprocessing the historical meteorological data. In this embodiment, the historical meteorological data includes temperature, humidity, wind speed, wind direction, air pressure and cloud cover; the preprocessing includes removing outliers, filling missing values ​​and normalizing. The data point value of the historical meteorological data after normalization is:

[0070]

[0071] In the formula, x normalized is the normalized data point value, x is a data point in the original data set, min(x) is the minimum value in the data set, and max(x) is the maximum value in the data set.

[0072] In order to further integrate spatial and temporal data, in this embodiment, a convolutional LSTM (ConvLSTM) model is used to predict the future precipitation data of the target area in the short term based on the preprocessed historical meteorological data, and the model is verified using indicators such as mean square error (MSE) and mean absolute error (MAE). Finally, the model parameters or structure are adjusted as needed, and the hyperparameters are adjusted in time to optimize the model. In this embodiment, the target area is a mountainous city.

[0073] S400, simulation of rainfall runoff in mountainous cities: according to the characteristics of watershed distribution, the watershed in the target area is divided into several simulation calculation units; combined with the attribute characteristics of each simulation calculation unit and the future precipitation data of the target area and the urban upstream catchment area, rainfall runoff simulation is performed on each simulation calculation unit, and the river confluence runoff in each simulation calculation unit is analyzed. Specifically, the attribute characteristics include one or more of mountain terrain characteristics, soil characteristics, land use characteristics, slope characteristics and slope aspect characteristics. In this embodiment, the attribute characteristics include mountain terrain characteristics, soil characteristics, land use characteristics, slope characteristics and slope aspect characteristics. The rainfall runoff simulation includes precipitation interception simulation, soil infiltration simulation, rainfall runoff simulation, slope runoff simulation and river confluence simulation. In this embodiment, the rainfall runoff simulation includes rainfall runoff simulation, slope runoff simulation and river confluence simulation.

[0074] The rainfall runoff simulation is used to analyze the instantaneous infiltration rate of water. The calculation formula of the instantaneous infiltration rate is as follows:

[0075]

[0076] In the formula, F is the instantaneous infiltration rate, Δh represents the change in soil moisture content, Δt represents the time interval, and K s is the saturated hydraulic conductivity of the soil, t is the duration of rainfall, h s is the saturated water head of the soil;

[0077] The slope runoff simulation is used to analyze the slope runoff volume. The calculation formula of the slope runoff volume is as follows:

[0078]

[0079] In the formula, Q slope is the slope runoff, R is the effective rainfall, I a is the initial loss, K is the soil permeability coefficient;

[0080] The river confluence simulation is used to analyze the river confluence runoff. The calculation formula of the river confluence runoff is as follows:

[0081]

[0082] Where Q(t) is the runoff of the river at time t', k i is the weight coefficient of the i-th time step, Δt′ is the time step, and R(t′-iΔt′) represents the surface runoff in the i-th time step.

[0083] S500 uses the calculated instantaneous infiltration rate, slope runoff, river runoff, predicted future precipitation data, environmental data of the target area, and spatial data of the flood-prone area as inputs to the flood evolution model, outputs the change process of water level and flow, constructs a simulation of flood evolution that fully considers upstream water, downstream regulation, mountain river terrain, future short-term heavy rainfall and other factors, predicts the propagation process of floods in mountain rivers, and thus accurately describes the flood peak transit route. The specific steps are as follows:

[0084] Simulation of flood evolution in mountainous rivers: The upstream water inflow, downstream water storage conditions and mountainous river terrain of the river area in each simulation calculation unit are analyzed separately and converted into river boundary conditions; in this embodiment, the river boundary conditions include river flow conditions, water storage conditions and flow rate conditions.

[0085] The river flow conditions are:

[0086] Q 下游 =Q 上游 +Q 山区流域

[0087] In the formula, Q 下游 Q is the flow generated by the downstream regulation of the simulation calculation unit; 上游 is the flow from the upstream of the simulation computing unit; Q 山区流域 To simulate the flow rate within the calculation unit;

[0088] The water storage conditions are:

[0089] V t+1 =V t +Q in ×Δt-Q out ×Δt

[0090] Where V t+1 is the reservoir water storage capacity at the next time step, V t is the reservoir water storage capacity at the current time step, Q in is the flow into the reservoir, Q out is the flow out of the reservoir, Δt is the time step;

[0091] The flow rate conditions are:

[0092]

[0093] Where v is the lateral velocity of the water flow in the river, n s is the Manning roughness coefficient, R s is the hydraulic radius and S is the slope of the riverbed.

[0094] A flood evolution model is constructed, and based on the river boundary conditions, the river shallow water equation is used to predict the propagation process of floods in the river area within each simulation calculation unit.

[0095] The shallow water equation for the river channel is:

[0096]

[0097] In the formula, It represents the rate of change of the amount of water passing through a fixed point per unit time in the x direction; It represents the rate of change of the amount of water passing through a fixed point per unit time in the y direction; represents the horizontal momentum hu in the x direction 2 With potential energy The rate of change of the sum of with spatial position; represents the horizontal momentum hu in the y direction 2 With potential energy The rate of change of the sum of with spatial position; It represents the rate of change of horizontal momentum in the y direction with spatial position; It represents the rate of change of horizontal momentum in the x direction with spatial position; represents the gravity effect caused by the change of riverbed elevation z in the x direction; represents the gravity effect caused by the change of riverbed elevation z in the y direction; represents the resistance term generated by riverbed friction in the x direction; represents the resistance term generated by riverbed friction in the y direction; represents the rate of change of water depth h with time t; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the x direction; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the y direction.

[0098] Simulation of the flooding process of mountainous cities based on the hydrodynamic model: According to the three-dimensional terrain model of mountainous cities, the building parameters and urban drainage system data in each simulation calculation unit are analyzed separately. In the process of urban flooding, the influence of buildings and urban drainage systems on water flow is a very important factor. Among them, the existence of buildings will change the path of water flow, slow down the speed of water flow, and may cause the water flow to bypass obstacles to form local eddy areas. The urban drainage system will directly affect the change of surface water level. Therefore, in this embodiment, in order to more accurately simulate the impact of buildings and drainage systems on water flow in urban environments, the building parameters and urban drainage system data are converted into urban boundary conditions, and the standard shallow water equations are corrected, thereby achieving a detailed prediction of the flooding situation of specific areas such as urban streets and underground spaces. In this embodiment, the urban boundary conditions include friction conditions and drainage system flow conditions, specifically:

[0099] Consider the impact of buildings: The presence of buildings will change the water flow path, slow down the water flow, and may cause the water flow to bypass obstacles to form local eddy areas. By introducing a resistance term to simulate (the resistance term is determined based on the flow velocity and the characteristics of the building), the friction condition is obtained:

[0100] F b =-C b ·ρ·A·|u|·u

[0101] In the formula, F b is the resistance term between water flow and buildings, C b is the drag coefficient of the building, ρ is the density of the water flow, A is the vertical projection area of ​​the building, and u is the velocity vector of the water flow;

[0102] Consider the impact of the urban drainage system: by removing part of the water volume to lower the surface water level, a source term Q is introduced into the continuity equation d To express the effect of the drainage system, that is, to introduce the drainage system flow condition:

[0103] Q d =k d ·h

[0104] In the formula, Q d is the flow through the urban drainage system, k d is the conductivity coefficient of water flow, and h is the water depth.

[0105] The flood evolution model is also used to predict the propagation process of floods in urban areas within each simulation calculation unit based on urban boundary conditions through the urban shallow water equation, and to predict the inundation range, average water depth and inundation range development speed of flood disasters.

[0106] The urban shallow water equation is:

[0107]

[0108] In the formula, F x is the component of the resistance caused by the building in the x direction; F y is the component of the drag caused by the building in the y direction.

[0109] S600: Evaluate the risk level of flooding disasters according to the prediction results of the flood evolution model, and generate a corresponding emergency plan.

[0110] S601, based on the predicted inundation range, average water depth and inundation range development speed, as well as the drainage capacity of the target area, taking into account the number of affected people, expected economic losses, and the impact on key infrastructure, combined with historical data and risk assessment results, the risk level and warning level of inundation disasters are divided. The division method is shown in Table 1:

[0111] Table 1 Reference table for flood disaster classification warning

[0112]

[0113] S602, according to the warning level of the flooding disaster, call the emergency plan in the preset emergency response plan library. The preset emergency response plan library contains several emergency plans, each of which corresponds to a corresponding warning level and includes evacuation route planning and rescue resource deployment, providing decision support for relevant rescue agencies.

[0114] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme is not described in detail here. Ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the scope of protection of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A flood disaster inundation prediction and graded early warning method considering the flood peak process, characterized by: Includes the following: Obtaining environmental data of the target area, including historical remote sensing images, measured waterlogging data, historical meteorological data, and watershed distribution characteristics; Based on the historical remote sensing images of the target area and the measured data of waterlogging, the spatial data of flood-prone areas are constructed; Preprocess the historical meteorological data and predict the future precipitation data of the target area based on the preprocessed historical meteorological data; According to the characteristics of watershed distribution, the watershed in the target area is divided into several simulation calculation units; combined with the attribute characteristics of each simulation calculation unit and the future precipitation data of the target area, rainfall runoff simulation is performed on each simulation calculation unit, and the river runoff in each simulation calculation unit is analyzed; Analyze the upstream water volume, downstream regulation and storage conditions, and mountain river terrain of each simulation unit, and convert them into river boundary conditions; analyze the building parameters and urban drainage system data in each simulation unit, and convert them into urban boundary conditions; A flood evolution model is constructed, and based on the river boundary conditions, the river shallow water equation is used to predict the propagation process of floods in the river area within each simulation calculation unit; the flood evolution model is also used to predict the propagation process of floods in the urban area within each simulation calculation unit based on the city boundary conditions through the city shallow water equation.

2. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The river boundary conditions include river flow conditions, water storage conditions and flow velocity conditions; The river flow conditions are: Q 下游 =Q 上游 +Q 山区流域 In the formula, Q 下游 Q is the flow generated by the downstream regulation of the simulation calculation unit; 上游 is the flow from the upstream of the simulation computing unit; Q 山区流域 To simulate the flow rate within the calculation unit; The water storage conditions are: V t+1 =V t +Q in ×Δt-Q out ×Δt Where V t+1 is the reservoir water storage capacity at the next time step, V t is the reservoir water storage capacity at the current time step, Q in is the flow into the reservoir, Q out is the flow out of the reservoir, Δt is the time step; The flow rate conditions are: Where v is the lateral velocity of the water flow in the river, n s is the Manning roughness coefficient, R s is the hydraulic radius and S is the slope of the riverbed.

3. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 2 is characterized by: The shallow water equation for the river channel is: In the formula, It represents the rate of change of the amount of water passing through a fixed point per unit time in the x direction; It represents the rate of change of the amount of water passing through a fixed point per unit time in the y direction; represents the horizontal momentum hu in the x direction 2 With potential energy The rate of change of the sum of with spatial position; represents the horizontal momentum hu in the y direction 2 With potential energy The rate of change of the sum of with spatial position; It represents the rate of change of horizontal momentum in the y direction with spatial position; It represents the rate of change of horizontal momentum in the x direction with spatial position; represents the gravity effect caused by the change of riverbed elevation z in the x direction; represents the gravity effect caused by the change of riverbed elevation z in the y direction; represents the resistance term generated by riverbed friction in the x direction; represents the resistance term generated by riverbed friction in the y direction; represents the rate of change of water depth h with time t; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the x direction; It represents the rate of change of the amount of water passing through a river channel of unit width per unit time in the y direction.

4. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 3 is characterized by: The urban boundary conditions include friction conditions and drainage system flow conditions; The friction conditions are: F b =-C b ·ρ·A·|u|·u In the formula, F b is the resistance term between water flow and buildings, C b is the drag coefficient of the building, ρ is the density of the water flow, A is the vertical projection area of ​​the building, and u is the velocity vector of the water flow; The flow conditions of the drainage system are: Q d =k d ·h In the formula, Q d is the flow through the urban drainage system, k d is the conductivity coefficient of water flow, and h is the water depth.

5. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 4 is characterized by: The urban shallow water equation is: In the formula, F x is the component of the resistance caused by the building in the x direction; F y is the component of the drag caused by the building in the y direction.

6. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The rainfall runoff simulation includes rainfall runoff simulation, slope runoff simulation and river confluence simulation; The rainfall runoff simulation is used to analyze the instantaneous infiltration rate of water. The calculation formula of the instantaneous infiltration rate is as follows: In the formula, F is the instantaneous infiltration rate, Δh represents the change in soil moisture content, Δt represents the time interval, and K s is the saturated hydraulic conductivity of the soil, t is the duration of rainfall, h s is the saturated water head of the soil; The slope runoff simulation is used to analyze the slope runoff volume. The calculation formula of the slope runoff volume is as follows: In the formula, Q slope is the slope runoff, R is the effective rainfall, I a is the initial loss, K is the soil permeability coefficient; The river confluence simulation is used to analyze the river confluence runoff. The calculation formula of the river confluence runoff is as follows: Where Q(t) is the runoff of the river at time t', k i is the weight coefficient of the i-th time step, Δt′ is the time step, and R(t′-iΔt′) represents the surface runoff in the i-th time step.

7. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The preprocessing includes removing outliers, filling missing values ​​and normalization. The data point values ​​of the historical meteorological data after normalization are: In the formula, x normalized is the normalized data point value, x is a data point in the original data set, min(x) is the minimum value in the data set, and max(x) is the maximum value in the data set.

8. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The environmental data also includes digital elevation model data; Constructing spatial data of flood-prone areas includes: Analyze the flood inundation scope of historical flood disaster areas based on historical remote sensing images and measured waterlogging data; Based on the flood inundation range of historical flood disaster areas, the flood-prone areas are analyzed and spatial data of flood-prone areas are constructed.

9. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The method also includes the following contents: evaluating the risk level of flooding disasters according to the prediction results of the flood evolution model, and generating corresponding emergency plans.

10. The flood disaster inundation prediction and graded early warning method considering the flood peak process according to claim 1 is characterized by: The attribute characteristics include one or more of mountain terrain characteristics, soil characteristics, land use characteristics, slope characteristics and slope aspect characteristics.

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