A method for simulating typhoon-induced debris flow motion considering spatiotemporal rainfall processes

Abstract

The present invention provides a method for simulating the movement of typhoon-storm debris flow considering the spatiotemporal rainfall process, which iteratively performs the following calculations until the convergence condition is met: decomposing the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term, wherein: the mass flux term calculates the contribution of fluid movement to mud depth through divergence; the rainfall intrusion term is calculated through the spatiotemporal rainfall distribution function. q w Dynamically correct mud depth; calculate the volume concentration of the current time step based on the updated mud depth distribution, and dynamically correct the turbulent resistance coefficient of the rheological model through an exponential function according to the volume concentration; calculate the debris flow friction resistance based on the corrected rheological model, solve the momentum equation, drive the SPH particle motion, and output the spatiotemporal evolution results.

Description

Technical Field

[0001] The present invention belongs to the technical field of geological disaster dynamics analysis and simulation, and in particular relates to a method for simulating the movement of typhoon-storm-type debris flows taking into account the temporal and spatial rainfall process. Background Art

[0002] The smoothed particle hydrodynamics (SPH) method, a meshless particle-based method, has been widely used in geological hazard simulation in recent years, demonstrating unique advantages in analyzing the evolution of hazards such as debris flows and landslides, which involve large deformations and complex flows. However, its application to typhoon-induced debris flows still faces significant challenges. Traditional simulation methods often assume a static environment, such as using a fixed time step or uniformly distributed rainfall input parameters. These methods fail to reflect the dynamic characteristics of rainfall intensity, which fluctuates dramatically over space and time in typhoon-induced debris flows. These methods typically describe the rheological behavior of debris flows using simplified empirical formulas (such as the Voellmy model). However, these frictional resistance parameters are often set to fixed values, making them unable to adapt to the heterogeneity of soil composition caused by changes in soil moisture content due to heavy rainfall intrusion. While existing studies have attempted to incorporate multiphase flow models or simulate erosion effects, they lack detailed modeling of the dynamic coupling between the temporal and spatial distribution of rainfall and the volume concentration of debris flows. This results in significant deviations from actual survey data in key metrics such as path prediction and accumulation range determination. Furthermore, most methods rely on offline data input, failing to achieve real-time interaction between rainfall monitoring data and simulation processes, limiting the timeliness of disaster warnings. Although some improved models attempt to enhance terrain coupling accuracy through GIS data, traditional methods still lack effective characterization of the dynamic evolution of the solid-liquid two-phase rheological properties of debris flows as rainfall intrusion occurs under the short-duration, high-intensity rainfall scenarios characteristic of typhoons and rainstorms. Summary of the Invention

[0003] In response to the defects and shortcomings of the existing technology, the present invention provides a method and system for simulating the movement of typhoon-storm debris flows that takes into account the spatiotemporal rainfall process. By decomposing the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term, the dynamic coupling of the spatiotemporal distribution of rainfall and the volume concentration of the debris flow is achieved. Among them, the mass flux term calculates the mud depth change based on the fluid motion divergence, while the rainfall intrusion term dynamically corrects the mud depth distribution through the spatiotemporal distribution function, breaking through the limitations of static rainfall input in traditional methods; combined with the improved Voellmy rheological model, the turbulent resistance coefficient is adjusted in real time using an exponential function driven by volume concentration, solving the defect that the fixed parameters of the traditional model cannot adapt to the dynamic changes in the solid-liquid ratio of the soil under heavy rain scenarios. Through the step-by-step iterative calculation process, the mud depth, volume concentration and friction resistance are updated in sequence, and finally the SPH particle motion is driven and high-precision spatiotemporal evolution results are output, realizing a refined simulation of the movement path, accumulation range and rheological characteristics of typhoon-storm-type debris flows, and the simulation accuracy is improved by more than 20% compared with the existing technology.

[0004] The technical solution specifically adopted by the present invention to solve the technical problem is:

[0005] A method for simulating typhoon-induced debris flow motion considering the spatiotemporal rainfall process:

[0006] The following calculations are performed iteratively until convergence conditions are met:

[0007] The average mud depth increment of the continuity equation is decomposed into a mass flux term and a rainfall intrusion term, where:

[0008] The mass flux term calculates the contribution of fluid motion to mud depth via divergence;

[0009] The rainfall intrusion term is expressed as the spatiotemporal rainfall distribution function q w Dynamic correction of mud depth;

[0010] The volume concentration of the current time step is calculated based on the updated mud depth distribution, and the turbulent resistance coefficient of the rheological model is dynamically corrected by an exponential function according to the volume concentration;

[0011] The friction resistance of debris flow is calculated based on the modified rheological model, the momentum equation is solved, the SPH particles are driven to move, and the spatiotemporal evolution results are output.

[0012] Furthermore, the mass flux term for calculating the average mud depth increment for the SPH particle numbered ip is specifically:

[0013]

[0014] in, is the average depth of the particle at time step n, is the velocity vector of the particle at time step n, div() is the divergence operator;

[0015] The rainfall intrusion term for calculating the average mud depth increment for the SPH particle numbered ip is specifically:

[0016]

[0017] in, is the spatiotemporal rainfall distribution function, is the coordinate of the particle, and t represents time.

[0018] Furthermore, the volume concentration is calculated by the following formula:

[0019]

[0020] in, is the average mud depth distribution of debris flow at time step n+1 of particle ip; is the equivalent depth distribution of debris flow water content at time step n+1 of particle ip;

[0021]

[0022] in, is the average mud depth distribution of debris flow at time step n of particle ip, dt is the calculation time step;

[0023]

[0024] in, is the equivalent depth distribution of debris flow water content at time step n of particle ip.

[0025] Furthermore, the formula for dynamically correcting the turbulent drag coefficient of the rheological model using an exponential function is:

[0026]

[0027] in, 、 is the soil consolidation parameter, and exp() is the exponential function.

[0028] Furthermore, the debris flow friction resistance τ ip The calculation formula is:

[0029]

[0030] in, τ ip is the bottom friction resistance of the ip particle, μ is the viscous drag coefficient, σ is the normal stress, ρ is the density and g is the acceleration due to gravity.

[0031] Furthermore, before executing the decomposition of the average mud depth increment of the continuity equation into the mass flux term and the rainfall intrusion term, the method further includes:

[0032] Generate debris flow particles based on geological survey data;

[0033] A background mesh is established and penetration boundary conditions are applied to constrain the range of particle motion.

[0034] Furthermore, the convergence conditions include:

[0035] The global particle minimum displacement increment is less than the set threshold;

[0036] The maximum calculation time exceeds the set value.

[0037] And, a typhoon rainstorm debris flow motion simulation system for implementing the above method, comprising:

[0038] The generation module generates debris flow particles based on geological survey data, establishes background grids and applies boundary conditions, and inputs spatiotemporal rainfall distribution functions;

[0039] The iterative calculation module uses the step-by-step method to calculate the average mud depth distribution of the debris flow in the n+1 time step; calculates the volume concentration of the current time step, and calculates the friction resistance of the debris flow based on the improved Voellmy rheological model; calculates the momentum equation, updates the position of the debris flow SPH particles, and enters the next time step or ends the calculation based on the convergence conditions.

[0040] And, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0041] A non-transitory computer-readable storage medium stores a computer program, which implements the steps of the method described above when executed by a processor.

[0042] Compared with the existing technology, the present invention and its preferred embodiment include at least the following beneficial effects: First, by decomposing the continuity equation into mass flux terms and rainfall intrusion terms, the limitation of static rainfall input of the traditional method is broken through, the dynamic coupling of the spatiotemporal distribution of rainfall and the volume concentration of debris flow is realized, and the spatiotemporal resolution of the simulation of the evolution process of debris flow movement under heavy rain scenarios is significantly improved; second, the innovative design of dynamically correcting the rheological model parameters based on volume concentration solves the defect that the fixed resistance coefficient in the traditional Voellmy model cannot adapt to the dynamic changes of the solid-liquid ratio of the soil, so that the calculation of friction resistance is more in line with the actual rheological characteristics; in addition, through the step-by-step iterative update of the technical chain of mud depth, volume concentration and friction resistance, a complete simulation closed loop from dynamic rainfall input to particle motion output is constructed, taking into account the balance between computational efficiency and accuracy in complex scenarios; finally, the systematic integration of the SPH particle method and the improved rheological model provides more universal and reliable technical support for the formulation of refined early warning and prevention strategies for typhoon and rainstorm debris flows. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0044] Figure 1 A flowchart of a method provided by an embodiment of the present invention.

[0045] Figure 2 Schematic diagram of the decomposition form of the debris flow continuity equation provided by an embodiment of the present invention.

[0046] Figure 3A comparison chart of debris flow simulation results with and without considering the impact of rainfall provided in an embodiment of the present invention.

[0047] Figure 4 This is a comparison chart of the results of considering and not considering the impact of process rainfall in the actual case simulation provided by the embodiment of the present invention.

[0048] Figure 5 This is a cross-sectional comparison of the results with and without considering the impact of process rainfall in the actual case simulation provided by the embodiment of the present invention.

[0049] Figure 6 This is a result verification diagram of considering the influence of process rainfall in the actual case simulation provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are given for detailed description:

[0051] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs.

[0052] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0053] To address the shortcomings and deficiencies of existing technologies, the present invention proposes a method for simulating the motion of typhoon-induced debris flows by defining a spatiotemporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing a modified Voellmy rheological model. This method effectively accounts for the impact of rainfall on debris flow mobility and, under specific conditions, improves the analytical accuracy of debris flow motion by over 20% compared to traditional methods. This method provides technical support for clarifying the evolutionary mechanisms of such disasters and developing scientifically effective disaster prevention strategies.

[0054] The technical problem to be solved by this invention is that current methods for simulating typhoon-induced debris flow motion ignore the impact of rainfall intrusion on rheological properties during debris flow development, resulting in large deviations in simulation results. A method and system for simulating typhoon-induced debris flow motion that considers the spatiotemporal rainfall process is proposed.

[0055] The present invention constructs a typhoon-rainstorm debris flow motion simulation method that takes into account the spatiotemporal rainfall process. It specifically introduces a spatiotemporal rainfall distribution function, adds a mass flux term to the continuity equation, and introduces an improved Voellmy rheological model. This solves the problem that existing analysis methods cannot consider the impact of the spatiotemporal distribution of rainfall, resulting in obvious deviations in the mobility evaluation of such disasters. This is of great value for understanding the mechanism of action of such debris flows and taking effective control measures.

[0056] The embodiment of the present invention addresses the problem that current particle-based methods such as the SPH method are unable to consider the impact of the spatiotemporal distribution of rainfall, resulting in obvious deviations in the evaluation of the mobility of typhoon-storm-type debris flows. By introducing a spatiotemporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model, the problem of traditional methods being unable to consider changes in the volume concentration of debris flows and making it difficult to effectively predict the mobility of debris flows is overcome. It can achieve effective simulation of typhoon-storm-type debris flow disasters in a given spatiotemporal rainfall process, laying an important foundation for understanding the mechanism of action of such debris flows and taking effective control measures. It mainly includes the following four steps:

[0057] Step 1: Generate debris flow particles based on geological survey data, establish background grids and apply boundary conditions, and input spatiotemporal rainfall distribution function;

[0058] Step 2: Apply the step-by-step method to calculate the average mud depth distribution of debris flow at time step n+1;

[0059] Step 3: Calculate the volume concentration of the current time step and calculate the friction resistance of the debris flow based on the improved Voellmy rheological model;

[0060] Step 4: Calculate the momentum equation, update the position of the debris flow SPH particles, and enter the next time step or end the calculation according to the convergence conditions.

[0061] In the specific implementation process, debris flow particles are generated according to geological survey data, background grids are established and boundary conditions are applied, and the spatial and temporal rainfall distribution function is input. , where x and y represent horizontal coordinates and t represents time, from which the rainfall intensity at any moment in any horizontal position can be obtained.

[0062] As the preferred design of this embodiment, the step-by-step method is used to calculate the average mud depth distribution of debris flow at n+1 time steps. Specifically include:

[0063] First, the average mud depth increment of the continuity equation is decomposed into the mass flux term and rainfall intrusion Two parts;

[0064] Then, the mass flux term of the average mud depth increment is calculated for the SPH particle numbered ip :

[0065] (1)

[0066] in, is the average depth of the particle at time step n, is the velocity vector of the particle at time step n, and div() is the divergence operator.

[0067] Then, the rainfall intrusion term of the average mud depth increment is calculated for the SPH particle numbered ip :

[0068] (2)

[0069] in, are the x and y coordinates of particle number ip.

[0070] Then, the average mud depth distribution of the debris flow at time step n+1 is calculated for the SPH particle numbered ip. :

[0071] (3)

[0072] in, is the average mud depth distribution of debris flow in n time steps, dt is the calculation time step.

[0073] As a preferred solution of this embodiment, the volume concentration of the current time step is calculated, and the magnitude of the friction resistance of the debris flow is calculated according to the improved Voellmy rheological model, specifically including:

[0074] First, the equivalent depth distribution of debris flow water content at time step n+1 is calculated for particle ip :

[0075] (4)

[0076] in, is the equivalent depth distribution of debris flow water content in time step n, is the spatiotemporal rainfall distribution function.

[0077] Then, calculate the debris flow volume concentration at time step n+1 :

[0078] (5)

[0079] Then, the turbulent drag coefficient is calculated under the change of volume concentration , exp() is the exponential function:

[0080] (6)

[0081] in, 、 is the soil consolidation parameter.

[0082] Then, calculate the friction resistance of debris flow :

[0083] (7)

[0084] in, is the bottom friction resistance of the ip particle, μ is the viscous drag coefficient, σ is the normal stress, ρ is the density, g is the acceleration due to gravity, is the velocity vector of particle ip, is the turbulent resistance coefficient considering the change of volume concentration.

[0085] As a preferred solution of this embodiment, the convergence condition is determined by the global particle minimum displacement increment and the maximum calculation time. When the global particle minimum displacement increment is less than the limit value or the maximum calculation time is greater than the limit value, the convergence condition is triggered to end the calculation.

[0086] Furthermore, a corresponding typhoon-induced rainstorm debris flow simulation system considering the spatiotemporal rainfall process is provided, comprising:

[0087] The generation module generates debris flow particles based on geological survey data, establishes background grids and applies boundary conditions, and inputs spatiotemporal rainfall distribution functions;

[0088] And iterative calculation module, used to perform the following iterative calculations:

[0089] The step-by-step method is used to calculate the average mud depth distribution of debris flow at the n+1 time step;

[0090] Calculate the volume concentration of the current time step and calculate the friction resistance of the debris flow based on the improved Voellmy rheological model;

[0091] Calculate the momentum equation, update the position of debris flow SPH particles, and enter the next time step or end the calculation according to the convergence conditions.

[0092] The following embodiment uses a specific debris flow case and follows the method flow ( Figure 1 ) for a detailed introduction:

[0093] Step 1: Generate 5000 debris flow particles based on the actual debris flow disaster geological survey data, establish a background grid of 500×500, set the infiltration boundary in the debris flow outflow direction, and input the spatiotemporal rainfall distribution function .

[0094] Step 2: Apply the step-by-step method to calculate the average mud depth distribution of debris flow at time step n+1 , which includes the following steps:

[0095] ① Taking the SPH particle numbered ip=1000 as an example, the average mud depth increment of the continuity equation is decomposed into the mass flux term and rainfall intrusion Two parts, the continuity equation form see Figure 2 ;

[0096] ② Calculate the mass flux term for the average mud depth increment :

[0097]

[0098] in, is the depth of the particle at time step n, is the velocity vector of the particle at time step n.

[0099] ③Calculate the rainfall intrusion term for the average mud depth increment If the rainfall is heavy At this time , then:

[0100]

[0101] in, are the x and y coordinates of particle ip=1000.

[0102] ④ Calculate the average mud depth distribution of the debris flow at time step n+1. For particle ip=1000:

[0103]

[0104] in, is the average mud depth distribution of debris flow in n time steps.

[0105] Step 3: Calculate the volume concentration of the current time step and calculate the friction resistance of the debris flow based on the improved Voellmy rheological model. Specifically include:

[0106] ① Taking particle ip=1000 as an example, calculate the equivalent depth distribution of debris flow water content at time step n+1 :

[0107]

[0108] in, is the equivalent depth distribution of debris flow water content in time step n, is the spatiotemporal rainfall distribution function.

[0109] ②Calculate the volume concentration of debris flow at time step n+1 :

[0110]

[0111] ③Calculate the turbulent resistance coefficient under changing volume concentration :

[0112]

[0113] ④Calculate the friction resistance of debris flow :

[0114]

[0115] in, is the bottom friction resistance of particle ip=1000, is the velocity vector of particle ip=1000, is the turbulent resistance coefficient considering the change of volume concentration.

[0116] Step 4: The convergence condition is determined by the global particle minimum displacement increment and the maximum calculation time. When the global particle minimum displacement increment is less than the limit value, which is set to 10 in this example, -3 m / s, or the maximum calculation time is greater than the limit, which is set to 5 hours in this example, i.e. 1.8×10 4 s. If any of the above conditions are met, the convergence condition is triggered. The comparison of debris flow simulation results with and without considering the process rainfall is shown in Figure 3 .

[0117] The following formula is used as the standard for evaluation:

[0118]

[0119] Among them I dep is the coverage rate, A real is the actual impact range of debris flow, A Model is the debris flow impact range obtained by model simulation.

[0120] The simulation was carried out based on a debris flow incident in a mountain village in the western part of a certain province. Figure 4 ) and topographic profiles ( Figure 5) It can be seen that compared with the simulation results without considering the influence of process rainfall, the simulation results after considering the influence of process rainfall show that the impact range of debris flow movement is increased, the height of static accumulation is reduced, and the coverage rate I dep The highest is 95.7%. And the simulation results after considering the influence of process rainfall are closer to the actual survey data (see Figure 6 This fully demonstrates that the simulation method of the present invention, which incorporates the spatiotemporal rainfall process, can more accurately depict the movement characteristics of typhoon-induced rainstorm debris flows under various terrain conditions. Compared with simulation methods that do not consider the impact of process rainfall, it can provide a more reliable decision-making basis for debris flow disaster prevention and control.

[0121] Considering the problem that current analysis methods cannot take into account the influence of the spatiotemporal distribution of rainfall, resulting in significant deviations in the evaluation of the mobility of typhoon-storm debris flows. The embodiment of the present invention overcomes the difficulty of traditional methods in effectively estimating the mobility of debris flows due to their inability to account for changes in the volume concentration of debris flows by introducing a spatiotemporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model. This can achieve effective simulation of typhoon-storm debris flow disasters in a given spatiotemporal rainfall process, laying an important foundation for understanding the mechanism of action of such debris flows and taking effective control measures.

[0122] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0123] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which, when executed by a processor, performs the above-described method. The storage medium may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0124] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0125] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other manner. Any person skilled in the art may utilize the above-disclosed technical content to modify or modify the present invention into equivalent embodiments. However, any simple modifications, equivalent variations, and modifications to the above embodiments that do not depart from the technical content of the present invention and are based on the technical essence of the present invention remain within the scope of protection of the present invention.

[0126] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive various other forms of a typhoon-rainstorm-type debris flow movement simulation method that takes into account the temporal and spatial rainfall process under the inspiration of the present invention. All equal changes and modifications made within the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for simulating typhoon-induced debris flow motion taking into account the spatiotemporal rainfall process, characterized by: The following calculations are performed iteratively until convergence conditions are met: The average mud depth increment of the continuity equation is decomposed into a mass flux term and a rainfall intrusion term, where: The mass flux term calculates the contribution of fluid motion to mud depth via divergence; The rainfall intrusion term is expressed by the spatiotemporal rainfall distribution function q w Dynamic correction of mud depth; The volume concentration of the current time step is calculated based on the updated mud depth distribution, and the turbulent resistance coefficient of the rheological model is dynamically corrected by an exponential function according to the volume concentration; Calculate the friction resistance of debris flow based on the modified rheological model, solve the momentum equation, drive the SPH particles to move, and output the spatiotemporal evolution results; The mass flux term for calculating the average mud depth increment for the SPH particle numbered ip is specifically: in, is the average depth of the particle at time step n, is the velocity vector of the particle at time step n, div() is the divergence operator; The rainfall intrusion term for calculating the average mud depth increment for the SPH particle numbered ip is specifically: in, is the spatiotemporal rainfall distribution function, is the coordinate of the particle, and t represents time.

2. The method for simulating typhoon-induced debris flow motion taking into account the spatiotemporal rainfall process according to claim 1, characterized in that: The volume concentration is calculated by the following formula: in, is the average mud depth distribution of debris flow at time step n+1 of particle ip; is the equivalent depth distribution of debris flow water content at time step n+1 of particle ip; in, is the average mud depth distribution of debris flow at time step n of particle No. ip, and dt is the calculation time step; in, is the equivalent depth distribution of debris flow water content at time step n of particle ip.

3. The method for simulating typhoon-induced debris flow motion taking into account the spatiotemporal rainfall process according to claim 2, characterized in that: The turbulent resistance coefficient of the rheological model is dynamically corrected by the exponential function The formula is: in, 、 is the soil consolidation parameter, and exp() is the exponential function.

4. The method for simulating typhoon-induced debris flow motion taking into account the spatiotemporal rainfall process according to claim 3, characterized in that: The debris flow friction resistance τ ip The calculation formula is: Among them, τ ip is the bottom friction resistance of particle ip, μ is the viscous resistance coefficient, σ is the normal stress, ρ is the density, and g is the acceleration due to gravity.

5. The method for simulating typhoon-induced debris flow motion considering the spatiotemporal rainfall process according to claim 1, characterized in that: Before executing the decomposition of the average mud depth increment of the continuity equation into the mass flux term and the rainfall intrusion term, the method further includes: Generate debris flow particles based on geological survey data; A background mesh is established and penetration boundary conditions are applied to constrain the range of particle motion.

6. The method for simulating typhoon-induced debris flow motion considering the spatiotemporal rainfall process according to claim 1, characterized in that: The convergence conditions include: The global particle minimum displacement increment is less than the set threshold; The maximum calculation time exceeds the set value.

7. A typhoon-rainstorm debris flow simulation system for implementing the method according to any one of claims 1 to 6, characterized in that: include: The generation module generates debris flow particles based on geological survey data, establishes background grids and applies boundary conditions, and inputs spatiotemporal rainfall distribution functions; The iterative calculation module uses the step-by-step method to calculate the average mud depth distribution of the debris flow in the n+1 time step; calculates the volume concentration of the current time step, and calculates the friction resistance of the debris flow based on the improved Voellmy rheological model; calculates the momentum equation, updates the position of the debris flow SPH particles, and enters the next time step or ends the calculation based on the convergence conditions.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 6 when executing the program.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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