Typhoon rainstorm debris flow motion simulation method considering space-time rainfall process

Abstract

The invention provides a typhoon rainstorm debris flow motion simulation method considering a space-time rainfall process, and the method comprises the steps: iteratively executing the following calculations until a convergence condition is satisfied: decomposing the average mud depth increment of a continuous equation into a mass flux item and a rainfall intrusion item, the mass flux item calculating the contribution of fluid motion to the mud depth through divergence; the rainfall intrusion item dynamically corrects the mud depth through a space-time rainfall distribution function qw; calculating the volume concentration of the current time step based on the updated mud depth distribution, and dynamically correcting the turbulence resistance coefficient of the rheological model through an exponential function according to the volume concentration; and calculating debris flow frictional resistance based on the corrected rheological model, solving a momentum equation, driving SPH particles to move and outputting a spatio-temporal evolution result.

Description

Technical Field

[0001] The present invention belongs to the technical field of dynamic analysis and simulation of geological disasters, and particularly relates to a method for simulating the movement of typhoon rainstorm-induced debris flows considering the spatio-temporal rainfall process. Background Technique

[0002] The Smoothed Particle Hydrodynamics (SPH) method, as a meshless particle method, has been widely used in the field of geological disaster simulation in recent years, especially showing unique advantages in the evolutionary analysis of disasters involving large deformations and complex flows such as debris flows and landslides. However, its specific application in typhoon rainstorm-induced debris flows still faces significant challenges. Traditional simulation methods are mostly based on static environment assumptions, such as using fixed time steps or uniformly distributed rainfall input parameters, and it is difficult to reflect the dynamic characteristics of the drastic fluctuations of rainfall intensity in space and time in the typhoon rainstorm scenario. Such methods usually describe the rheological behavior of debris flows through simplified empirical formulas (such as the Voellmy model), but their friction resistance parameters are often set as fixed values and cannot adapt to the heterogeneity of material composition caused by the change of soil moisture content due to the intrusion of rainstorms. Although existing studies have tried to introduce multiphase flow models or erosion effect simulations, there are still deficiencies in the refined modeling of the dynamic coupling of rainfall spatio-temporal distribution and debris flow volume concentration, resulting in significant deviations between the simulation results and the actual survey data in key indicators such as the prediction of the movement path and the determination of the deposition range. In addition, most methods rely on offline data input and fail to achieve real-time interaction between rainfall monitoring data and the simulation process, restricting the timeliness of disaster warning. Although some improved models attempt to enhance the terrain coupling accuracy through GIS data, in the short-duration and high-intensity rainfall scenarios unique to typhoon rainstorms, traditional methods still lack effective means to characterize the dynamic evolution law of the rheological properties of the solid-liquid two-phase of debris flows with the intrusion of rainfall. Summary of the Invention

[0003] Aiming at the defects and deficiencies existing in the prior art, the present invention provides a method and system for simulating the movement of typhoon rainstorm-induced debris flows considering the spatio-temporal 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 rainfall spatio-temporal distribution and debris flow volume concentration is realized. Among them, the mass flux term calculates the mud depth change based on the divergence of fluid motion, and the rainfall intrusion term dynamically corrects the mud depth distribution through a spatio-temporal distribution function, breaking through the limitations of static rainfall input in traditional methods; combined with an 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 traditional models cannot adapt to the dynamic changes of the solid-liquid ratio of the soil body in the rainstorm scenario. Through a step-by-step iterative calculation process, the mud depth, volume concentration, and friction resistance are updated in sequence, and finally the SPH particles are driven to move and high-precision spatio-temporal evolution results are output, realizing the refined simulation of typhoon rainstorm-induced debris flows in terms of movement path, deposition range, and rheological properties, with a simulation accuracy improvement of more than 20% compared with the prior art.

[0004] The technical solution specifically adopted by the present invention to solve its technical problems is as follows: A method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process: Iteratively perform the following calculations until the convergence condition is met: Decompose the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term, where: The mass flux term calculates the contribution of fluid motion to the mud depth through divergence; The rainfall intrusion term dynamically corrects the mud depth through the spatio-temporal rainfall distribution function q w Dynamic correction of the mud depth; Calculate the volume concentration at the current time step based on the updated mud depth distribution, and dynamically correct the turbulent drag coefficient of the rheological model according to the volume concentration through an exponential function; Calculate the debris flow frictional resistance based on the corrected rheological model, solve the momentum equation, drive the SPH particle motion, and output the spatio-temporal evolution results.

[0005] Further, the specific calculation of the mass flux term of the average mud depth increment for the SPH particle numbered ip is as follows:

[0006] Where, 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; The specific calculation of the rainfall intrusion term of the average mud depth increment for the SPH particle numbered ip is as follows:

[0007] Where, is the spatio-temporal rainfall distribution function, is the coordinate of the particle, and t represents time.

[0008] Further, the volume concentration is calculated by the following formula:

[0009] Where, is the average mud depth distribution of the debris flow at the (n + 1)-th time step of the ip-th particle; is the equivalent depth distribution of the water content of the debris flow at the (n + 1)-th time step of the ip-th particle;

[0010] Where, is the average mud depth distribution of the debris flow at the n-th time step of the ip-th particle, dtFor calculating the time step;

[0011] Wherein, is the equivalent depth distribution of the debris flow water content of the ip-th particle at the n-th time step.

[0012] Furthermore, the formula for dynamically correcting the turbulent drag coefficient of the rheological model through an exponential function is:

[0013] Wherein, and are soil consolidation parameters, and exp() is an exponential function.

[0014] Furthermore, the debris flow frictional resistance τ ip The calculation formula is:

[0015] Wherein, τ ip is the bottom frictional resistance of the ip-th particle, μ is the viscous drag coefficient, σ is the normal stress, ρ is the density, and g is the acceleration due to gravity.

[0016] Furthermore, before performing the decomposition of the average mud depth increment of the continuity equation into the mass flux term and the rainfall intrusion term, it also includes: Generating debris flow particles based on geological exploration data; Establishing a background grid and applying a permeable boundary condition to constrain the movement range of the particles.

[0017] Furthermore, the convergence conditions include: The minimum displacement increment of global particles is less than the set threshold; The maximum calculation time exceeds the set value.

[0018] And, a typhoon rainstorm type debris flow movement simulation system for implementing the method as described above, including: A generation module, which generates debris flow particles based on geological exploration data, establishes a background grid and applies boundary conditions, and inputs a spatio-temporal rainfall distribution function; An iterative calculation module, which calculates the average mud depth distribution of the debris flow at the n + 1 time step by applying the fractional step method; calculates the volume concentration at the current time step, calculates the magnitude of the debris flow frictional resistance according to the improved voellmy rheological model; calculates the momentum equation, updates the positions of the debris flow SPH particles, and enters the next time step or ends the calculation according to the convergence conditions.

[0019] In addition, an electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above-described method are implemented.

[0020] A non-transitory computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the steps of the above-described method are implemented.

[0021] Compared with the prior art, the present invention and its preferred solutions at least include the following beneficial effects: First, by decomposing the continuity equation into a mass flux term and a rainfall intrusion term, the limitation of the static rainfall input in the traditional method is broken through, and the dynamic coupling of the rainfall spatio-temporal distribution and the debris flow volume concentration is realized, significantly improving the spatio-temporal resolution of the simulation of the debris flow movement and evolution process under heavy rainfall scenarios; Second, based on the innovative design of dynamically correcting the rheological model parameters according to the volume concentration, the defect that the fixed resistance coefficient in the traditional Voellmy model cannot adapt to the dynamic change of the solid-liquid ratio of the soil mass is solved, making the calculation of the frictional resistance more in line with the actual rheological characteristics; In addition, through the technical chain of iteratively updating the mud depth, volume concentration, and frictional resistance by the step-by-step method, a complete simulation closed-loop from dynamic rainfall input to particle movement output is constructed, taking into account the balance between calculation 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 refined early warning and prevention strategy formulation of typhoon heavy rainfall-induced debris flows. Description of the Drawings

[0022] The present invention will be further described in detail below with reference to the drawings and specific embodiments: Figure 1 It is a flowchart of the method provided by the embodiment of the present invention.

[0023] Figure 2 It is a schematic diagram of the decomposition form of the debris flow continuity equation provided by the embodiment of the present invention.

[0024] Figure 3 It is a comparison diagram of the debris flow movement simulation results considering and not considering the influence of process rainfall provided by the embodiment of the present invention.

[0025] Figure 4 It is a comparison diagram of the results considering and not considering the influence of process rainfall in the actual case simulation provided by the embodiment of the present invention.

[0026] Figure 5 It is a cross-sectional comparison diagram of the results considering and not considering the influence of process rainfall in the actual case simulation provided by the embodiment of the present invention.

[0027] Figure 6 It 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 implementation manners

[0028] To make the features and advantages of the present invention more obvious and understandable, specific embodiments are given below and described in detail as follows: It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0029] 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 "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] Aiming at the defects and deficiencies existing in the prior art, the embodiments of the present invention propose a method for simulating the movement of typhoon rainstorm-induced debris flows considering the spatio-temporal rainfall process by defining a spatio-temporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model. This method can effectively consider the influence of process rainfall on the mobility of debris flows. Compared with traditional methods, it can improve the analysis accuracy of the debris flow movement process by more than 20% under specific conditions, providing technical support for clarifying the evolution mechanism of such disasters and formulating scientific and effective disaster prevention strategies.

[0031] The technical problem to be solved by the present invention is that the existing methods for simulating the movement of typhoon rainstorm-induced debris flows ignore the influence of rainfall intrusion on the rheology during the development of debris flows, resulting in relatively large deviations in simulation results. A method and system for simulating the movement of typhoon rainstorm-induced debris flows considering the spatio-temporal rainfall process are proposed.

[0032] The present invention constructs a method for simulating the movement of typhoon rainstorm-induced debris flows considering the spatio-temporal rainfall process, especially introducing a spatio-temporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model, solving the problem that the existing analysis methods have obvious deviations in the evaluation of the mobility of such disasters due to the inability to consider the influence of the spatio-temporal distribution of rainfall, and having important value for understanding the action mechanism of such debris flows and taking effective control measures.

[0033] In the embodiments of the present invention, aiming at the problem that the current particle-based methods such as the SPH method cannot consider the influence of the spatio-temporal distribution of rainfall, resulting in obvious deviations in the evaluation of the mobility of typhoon rainstorm-induced debris flows. By introducing a spatio-temporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model, it overcomes the difficulty of effectively predicting the mobility of debris flows in traditional methods due to the inability to consider the change of debris flow volume concentration. It can effectively simulate the typhoon rainstorm-induced debris flow disasters under a given spatio-temporal rainfall process, laying an important foundation for understanding the action mechanism of such debris flows and taking effective control measures. It mainly includes the following 4 steps: Step 1: Generate debris flow particles according to geological exploration data, establish a background grid and apply boundary conditions, and input the spatio-temporal rainfall distribution function; Step 2: Use the fractional step method to calculate the average mud depth distribution of the debris flow at the n+1 time step; Step 3: Calculate the volume concentration at the current time step, and calculate the magnitude of the frictional resistance of the debris flow according to the improved Voellmy rheological model; Step 4: Calculate the momentum equation, update the positions of the debris flow SPH particles, and enter the next time step or end the calculation according to the convergence condition.

[0034] In the specific implementation process, generate debris flow particles according to geological exploration data, establish a background grid and apply boundary conditions, and input the spatio-temporal rainfall distribution function , where x and y represent the horizontal plane coordinates, and t represents time, from which the rainfall intensity at any horizontal position at any moment can be obtained.

[0035] As the preferred design of this embodiment, use the fractional step method to calculate the average mud depth distribution of the debris flow at the n+1 time step Specifically include: First, decompose the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term two parts; Then, calculate the mass flux term of the average mud depth increment for the SPH particle numbered ip : (1) Among them, 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.

[0036] Then, calculate the rainfall intrusion term of the average mud depth increment for the SPH particle numbered ip : (2) Among them, They are the x and y coordinates of the ip-numbered particles.

[0037] Then, calculate the average mud depth distribution of debris flow at the (n + 1)-th time step for the SPH particles numbered ip. : (3) Wherein, is the average mud depth distribution of debris flow at the n-th time step, dt is the calculation time step size.

[0038] As a preferred solution of this embodiment, calculating the volume concentration at the current time step and calculating the magnitude of the debris flow frictional resistance according to the improved Voellmy rheological model specifically include: First, calculate the equivalent depth distribution of the debris flow water content at the (n + 1)-th time step for the ip-numbered particle. : (4) Wherein, is the equivalent depth distribution of the debris flow water content at the n-th time step, is the spatio-temporal rainfall distribution function.

[0039] Then, calculate the debris flow volume concentration at the (n + 1)-th time step : (5) Then, calculate the turbulent drag coefficient under the change of volume concentration , where exp() is the exponential function: (6) Wherein, , are the soil consolidation parameters.

[0040] Then, calculate the debris flow frictional resistance : (7) Wherein, is the bottom frictional resistance of the ip-numbered 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 the ip-numbered particle, is the turbulent drag coefficient considering the change of volume concentration.

[0041] As a preferred solution of this embodiment, the convergence condition is determined by the minimum global particle displacement increment and the maximum calculation time. When the minimum global particle 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.

[0042] And, a typhoon rainstorm type debris flow movement simulation system considering the spatio-temporal rainfall process is provided, including: A generation module, which generates debris flow particles according to geological exploration data, establishes a background grid and applies boundary conditions, and inputs a spatio-temporal rainfall distribution function; And an iterative calculation module, which is used to perform the following iterative calculations: Apply the fractional step method to calculate the average mud depth distribution of debris flow at the n+1 time step; Calculate the volume concentration at the current time step, and calculate the magnitude of the debris flow frictional resistance according to the improved Voellmy rheological model; Calculate the momentum equation, update the positions of the debris flow SPH particles, and enter the next time step or end the calculation according to the convergence condition.

[0043] In the following, through a specific debris flow case, the present embodiment will be introduced in detail according to the method flow ( Figure 1 ): Step 1: Generate 5000 debris flow particles according to the actual geological exploration data of the debris flow disaster, establish a background grid of 500×500, set a permeable boundary in the debris flow outflow direction, and input the spatio-temporal rainfall distribution function .

[0044] Step 2: Apply the fractional step method to calculate the average mud depth distribution of debris flow at the n+1 time step , including the following steps: ① Taking the SPH particle numbered ip=1000 as an example, decompose the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term two parts. The form of the continuity equation is shown in Figure 2 ; ② Calculate the mass flux term of the average mud depth increment :

[0045] Among them, is the depth of the particle at time step n, is the velocity vector of the particle at time step n.

[0046] ③ Calculate the rainfall intrusion term of the average mud depth increment . If the rainfall intensity is at this time, then there is:

[0047] Among them, are the x and y coordinates of the particle numbered ip=1000.

[0048] ④ Calculate the average mud depth distribution of debris flow at the n+1 time step. For particle ip = 1000, we have:

[0049] where, is the average mud depth distribution of debris flow at the n time step.

[0050] Step 3: Calculate the volume concentration at the current time step and calculate the magnitude of the frictional resistance of debris flow according to the improved Voellmy rheological model, which specifically includes: ① Taking particle ip = 1000 as an example, calculate the equivalent depth distribution of the water content of debris flow at the n+1 time step :

[0051] where, is the equivalent depth distribution of the water content of debris flow at the n time step, is the spatio-temporal rainfall distribution function.

[0052] ② Calculate the volume concentration of debris flow at the n+1 time step :

[0053] ③ Calculate the turbulent resistance coefficient under the change of volume concentration :

[0054] ④ Calculate the frictional resistance of debris flow :

[0055] where, is the bottom frictional resistance of particle ip = 1000, is the velocity vector of particle ip = 1000, is the turbulent resistance coefficient considering the change of volume concentration.

[0056] Step 4: The convergence condition is determined by the minimum displacement increment of global particles and the maximum calculation time. When the minimum displacement increment of global particles is less than the specified value, which is set to 10 -3 m / s in this example, or the maximum calculation time is greater than the specified value, which is set to 5 hours, i.e., 1.8×10 4 s in this example. If either of the above conditions is met, the convergence condition is triggered. The comparison of the simulation results of debris flow movement with and without considering the process rainfall can be seen in Figure 3 .

[0057] Refer to the following formula as the standard for evaluation:

[0058] where I dep is the coverage rate, A real is the actual influence range of debris flow, A Model is the debris flow influence range obtained by model simulation.

[0059] Taking the debris flow example that occurred in a mountain village in the western region of a certain province as the object, simulations were carried out. From the simulation result diagram ( Figure 4 ), and the topographic profile diagram ( 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 influence range of debris flow movement increases, the height at rest and accumulation decreases, and the coverage rate I dep is higher at 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 shows that the simulation method incorporating the spatio-temporal rainfall process in the present invention can more accurately depict the movement characteristics of typhoon rainstorm-induced debris flows under different terrain conditions. Compared with the simulation method without considering the influence of process rainfall, it can provide a more reliable decision-making basis for the prevention and control of debris flow disasters.

[0060] Considering the problem that the current analysis method has an obvious deviation in the evaluation of the mobility of typhoon rainstorm-induced debris flows due to the inability to consider the influence of the spatio-temporal distribution of rainfall. In the embodiments of the present invention, by introducing a spatio-temporal rainfall distribution function, adding a mass flux term to the continuity equation, and introducing an improved Voellmy rheological model, the difficulty in effectively predicting the mobility of debris flows caused by the inability of the traditional method to consider the change in debris flow volume concentration is overcome. It can achieve an effective simulation of typhoon rainstorm-induced debris flow disasters for a given spatio-temporal rainfall process, laying an important foundation for understanding the action mechanism of such debris flows and taking effective control measures.

[0061] Based on the same inventive concept, the present invention further 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 configured to execute the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application-Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is used to implement one or more instructions. Specifically, it is used to load and execute one or more instructions in the computer storage medium to implement the above method.

[0062] It should be further noted that, based on the same inventive concept, the present invention further provides a computer storage medium, on which a computer program is stored, and the computer program, when run by a processor, executes the above method. The storage medium may adopt 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, for example, but not be limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, the computer-readable storage medium may be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device.

[0063] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those with ordinary skills in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Words such as "comprising" or "including" mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connected" or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Upper", "lower", "left", "right", etc. are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0064] As described above, the above are only the preferred embodiments of the present invention, and are not limitations to the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications into equivalent embodiments with equivalent changes. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

[0065] The present invention is not limited to the above best mode. Anyone inspired by the present invention can obtain other various forms of a method for simulating the movement of typhoon rainstorm type debris flow considering the spatio-temporal rainfall process. All equal changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope covered by the present invention.

Claims

1. A method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process, characterized in that: Iteratively execute the following calculations until the convergence condition is met: Decompose the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term, where: The mass flux term calculates the contribution of fluid motion to the mud depth through divergence; The rainfall intrusion term dynamically corrects the mud depth through the spatio-temporal rainfall distribution function q w ​ Based on the updated mud depth distribution, calculate the volume concentration at the current time step, and dynamically correct the turbulent drag coefficient of the rheological model according to the volume concentration through an exponential function; Based on the corrected rheological model, calculate the debris flow frictional resistance, solve the momentum equation, drive the SPH particle motion, and output the spatio-temporal evolution result.

2. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 1, characterized in that: The specific calculation of the mass flux term of the average mud depth increment for the SPH particle numbered ip is: where, 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; The specific calculation of the rainfall intrusion term of the average mud depth increment for the SPH particle numbered ip is: Among them, is the spatio-temporal rainfall distribution function, is the coordinate of the particle, and t represents time.

3. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 2, characterized in that: The volume concentration is calculated by the following formula: Among them, is the average mud depth distribution of debris flow at the (n + 1)-th time step for the ip-th particle; is the equivalent depth distribution of the water content of debris flow at the (n + 1)-th time step for the ip-th particle; Among them, is the average mud depth distribution of debris flow at the n-th time step of the ip-th particle, dt is the calculation time step; Among them, is the equivalent depth distribution of the debris flow water body content of the ip-th particle at the n-th time step.

4. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 3, characterized in that: The formula for dynamically correcting the turbulent drag coefficient of the rheological model through an exponential function is: Among them, , are soil consolidation parameters, and exp() is an exponential function.

5. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 4, characterized in that: The debris flow frictional resistance τ ip The calculation formula is as follows: Among them, τ ip is the bottom friction resistance of the ip number particles, μ is the viscous resistance coefficient, σ is the normal stress, ρ is the density, and g is the acceleration due to gravity.

6. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 1, characterized in that: Before performing the decomposition of the average mud depth increment of the continuity equation into a mass flux term and a rainfall intrusion term, it further includes: Generate debris flow particles according to geological exploration data; Establish a background grid and apply a permeable boundary condition to constrain the particle movement range.

7. The method for simulating the movement of typhoon rainstorm-induced debris flow considering the spatio-temporal rainfall process according to claim 1, characterized in that: The convergence conditions include: The minimum displacement increment of global particles is less than the set threshold; The maximum calculation time exceeds the set value.

8. A typhoon and rainstorm type debris flow movement simulation system for implementing the method according to any one of claims 1-7, characterized in that, It includes: A generation module that generates debris flow particles according to geological exploration data, establishes a background grid and applies boundary conditions, and inputs the spatio-temporal rainfall distribution function; An iterative calculation module that calculates the average mud depth distribution of debris flow at the n + 1 time step using the fractional step method; calculates the volume concentration at the current time step, and calculates the magnitude of the debris flow frictional resistance according to the improved Voellmy rheological model; calculates the momentum equation, updates the positions of debris flow SPH particles, and enters the next time step or ends the calculation according to the convergence conditions.

9. An electronic device, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, wherein when the processor executes the program, it implements the steps of the method according to any one of claims 1 - 7.

10. A non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 - 7.

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