43 results about "Flash flood" patented technology

A flash flood simulation method includes: obtaining a water storage in a vegetation root zone and obtaining an actual evaporation at any point in the vegetation root zone within a target watershed; obtaining a total infiltration rate in an unsaturated zone based on an infiltration model; obtaining a saturation overland flow and an interflow based on a vertical distance from a wetting front to a slope surface; updating an average saturated groundwater table depth based on the interflow and the total infiltration rate of the unsaturated zone; constructing a flash flood model for the target watershed based on the water storage of the vegetation root zone, the actual evaporation, the total infiltration rate of the unsaturated zone, the saturation overland flow, the interflow, and the average saturated groundwater table depth; and simulating an event-based flood hydrograph of the target watershed based on the flash flood model for the target watershed.

The invention discloses a method, a product and equipment for generating a mountain torrent disaster dynamic plan based on causal inference, and belongs to the technical field of mountain torrent disaster monitoring. The method comprises the following steps: S1, acquiring multi-source data, and extracting causal features of the multi-source data; during extraction, dual robust data deviation elimination is realized based on a tendency scoring model and a result regression model; s2, performing dynamic causal graph modeling based on the extracted causal features and a historical disaster data set, and updating the weight to obtain a causal graph with a time sequence weight; s3, determining a current disaster situation state according to the causal diagram information, and performing anti-fact plan generation in combination with a preset intervention measure set to obtain an optimal plan set; and S4, performing multi-department collaborative execution based on the optimal plan set. According to the method, the pain point problems of passive response, lack of causal support and cross-department collaboration low efficiency of a traditional mountain torrent plan can be solved.

The invention discloses a mountain torrent early warning rainfall threshold dynamic adjustment method and system, and relates to the technical field of hydrological early warning, and the method comprises the steps: obtaining basic rainfall data and a basic early warning threshold of a target region; according to the basic rainfall data, performing calculation to obtain a multi-factor correction factor; the multi-factor correction factors comprise an early-stage wettability correction factor, a rainfall intensity correction factor and a rain pattern mode correction factor; calculating to obtain a comprehensive correction factor according to the multi-factor correction factor; according to the comprehensive correction factor and the basic early warning threshold value, calculating to obtain a dynamic early warning threshold value; the dynamic early warning threshold value comprises a ready transfer dynamic early warning threshold value and an immediate transfer dynamic early warning threshold value; and determining a rainfall early warning level according to the dynamic early warning threshold and the real-time rainfall. According to the invention, the early warning threshold can be dynamically adjusted according to the real-time working condition, and the accuracy and timeliness of mountain torrent early warning are improved.

This invention discloses a flash flood and debris flow monitoring device based on phased array radar technology, comprising a base, a support plate, and a mounting plate. A column is rotatably connected to the top of the base, and a fixing groove is provided on the top of the base, within which a fixing mechanism corresponding to the column is fixedly connected. A support rod is slidably inserted into the top of the column, and the top of the support rod is fixedly connected to the bottom of the support plate. A support block is fixedly connected to one side of the column, and the support block is connected to the support plate via turnbuckles. A fixing rod is rotatably connected to the top of the support plate via a rotating rod, and the top of the fixing rod is fixedly connected to the bottom of the mounting plate. A sliding groove is provided on the top of the support plate, within which a screw is rotatably connected. A slider is threaded onto the screw, and the slider is connected to the mounting plate via a transmission rod. This invention, through the setting of multiple adjustment mechanisms, allows the monitoring device to be freely adjusted according to actual installation needs, thereby effectively improving the installation and usage effect of the monitoring device.

The invention discloses a mountain torrent disaster early warning method, device and equipment and a medium, and relates to the technical field of hydrological monitoring and disaster early warning. The method comprises the steps of determining theoretical confluence time according to static attributes of a target drainage basin, determining an observation window of a rainfall event according to the theoretical confluence time, and performing sliding window analysis on a rainfall process of the rainfall event by using the observation window to obtain accumulated rainfall in the observation window, according to runoff reduction analysis, the accumulated rainfall is converted into effective peak flow, the effective peak flow is compared with disaster-causing flow, and early warning is given out according to a comparison result. According to the early warning method, the observation window is associated with the flow concentration time of the drainage basin, and the peak rainfall related to the flow concentration time of the drainage basin is captured based on the accumulated rainfall counted by the observation window, so that the rainfall process is prevented from being split by statistics in a fixed time period, and the early warning effectiveness is improved.

The invention relates to the technical field of disaster early warning processing, in particular to a mountain torrent disaster early warning system based on deep learning and air-space-ground integrated perception. The system comprises the following modules: a space-air-ground sensing module, an edge calculation preprocessing module, a deep learning prediction module and an intelligent decision and early warning module. Wherein the air-space-ground sensing module is used for collecting multi-source data; wherein the multi-source data comprises earth surface deformation data obtained through a spaceborne synthetic aperture radar, high-precision topographic data obtained through an unmanned aerial vehicle laser radar, hydrological sensing data obtained through a ground internet-of-things distributed sensor, and meteorological numerical forecasting data obtained through a meteorological data interface. Through air-space-ground integrated perception, physical constraint deep learning and edge intelligence technologies, mountain torrent multi-source data collaborative acquisition and accurate mountain torrent disaster prediction are realized, so that the comprehensiveness, reliability and timeliness of mountain torrent disaster early warning are improved.

The invention discloses a mountain torrent disaster risk avoiding guidance and emergency command system and method based on edge computing, and relates to the technical field of mountain torrent disaster dispatch, in the method, an edge disaster sensing and gathering module gathers disaster dynamic data and positioning information on a target monitoring mountainous area map, and a comprehensive disaster situation map is constructed; an intelligent risk-avoiding path planning module automatically plans a risk-avoiding path by using a dynamic cost grid algorithm and an A path-finding algorithm according to the comprehensive disaster situation map, and generates a path instruction; a self-adaptive emergency command decision module automatically matches a preset emergency plan to generate a command instruction according to the real-time submerging range, the early warning level and the affected population density of each disaster area; and the multi-mode guide instruction issuing module sends a path instruction and a command instruction. According to the invention, the efficiency and rationality of mountain torrent disaster risk avoiding guidance and emergency command can be improved.

This application discloses a dynamic decision-making method and system for flash floods and debris flows based on multi-agent and LLM (Limited Language Model), belonging to the field of emergency management and intelligent decision-making technology. This method constructs an intelligent decision-making architecture based on a large model and multi-agent collaboration. It solves the execution challenges of complex disaster tasks through the division of labor and cooperation among multiple agents, and overcomes the decision-making limitations of traditional systems by leveraging the deep reasoning capabilities of a large language model. Specifically, the multi-agent collaborative framework decomposes disaster prevention and control decisions into sub-tasks such as intent parsing, contingency plan retrieval, spatial analysis, data acquisition, and analysis and prediction. Each functional agent focuses on its area of ​​expertise, improving the efficiency and accuracy of task execution. The agent communication protocol ensures efficient information interaction and collaborative scheduling between modules, realizing fully automated processing from task input to data output.

The application discloses a kind of mountain torrent risk prediction big model's partition classification parallel training method, the method includes the following steps: step 1, mountain torrent disaster sample big data construction;Step 2, mountain torrent disaster is classified and input-output strategy is formulated;Step 3, partition classification carries out big model parallel training;Step 4, big model input strategy adjustment;Step 5, interactive automatic optimization big model parameter.The method disclosed in the application improves the generalization ability and prediction accuracy of mountain torrent risk prediction big model by partition classification of sample big data;Proposed mountain torrent risk prediction big model parallel training method improves training efficiency;Using the characteristics of big model back propagation, calculate the relative contribution of input elements to mountain torrent disaster, guide to simplify input elements, on the basis of ensuring prediction accuracy, light weight mountain torrent risk prediction big model.

The invention relates to the technical field of mountain torrent monitoring, in particular to a mountain torrent disaster real-time monitoring method and system integrating radar and video. Comprising the following steps: respectively acquiring a water velocity signal and a mountain torrent region image sequence through radar equipment and video equipment, and aligning the frequency difference of acquired data through a timestamp calibration mechanism to form a multi-source data set with preliminarily aligned time and space; motion feature vectors and boundary contour features are extracted from the data set, filtering smoothing processing is carried out on the motion features, and noise is removed; correcting timestamp offset, ensuring data time unification, and associating motion features with boundary contour features through space mapping to generate a fusion feature map; calculating the corresponding relation between the water velocity and the boundary contour through the fusion feature map, generating a dynamic hydrological parameter distribution map, marking a high-risk disaster range, generating a comprehensive monitoring report, and determining the mountain torrent disaster state in real time. According to the invention, the real-time monitoring precision and early warning capability of mountain torrent disasters are effectively improved.

The invention discloses a mountain torrent disaster comprehensive risk prediction method and system based on multi-source data, and relates to the technical field of mountain torrent disaster risk prediction.The method comprises the steps of multi-source data acquisition, multi-source data analysis and mountain torrent disaster prediction feedback, the multi-source data is accurately acquired, then the state corresponding to a region is evaluated, and the risk prediction accuracy is improved. And predicting whether the mountain torrent disaster occurs in the region and the disaster level, analyzing to obtain early warning maintenance of the mountain torrent disaster corresponding to the region, executing negative hidden danger cost pre-simulation of the adopted maintenance set under the mountain torrent disaster risk level, and evaluating to obtain the cost of the adopted early warning maintenance of the mountain torrent disaster corresponding to the region. And adaptive early warning maintenance under the corresponding mountain torrent disaster of the region is obtained through screening, so that accurate prediction of the corresponding mountain torrent disaster risk of the region is realized, effective measures are taken for prevention of a prediction result in time, and dangerous influence and risk loss caused by the mountain torrent disaster are reduced.

This invention discloses a method for early warning of flash floods in important villages based on small reservoir hydrological and rainfall monitoring. The method first collects data from the study area, constructing a multi-source heterogeneous data fusion system and a hydrological-topographic-socioeconomic correlation network for the study area. Then, it constructs spatial location and water flow path correlations between small reservoirs and important villages, generating inundation range maps and delineating risk zones based on the topography, building layout, and set water level thresholds of the important villages. A reservoir-river-village hydrodynamic coupling model is constructed to calculate the correlation between small reservoir monitoring indicators and village disaster events, and this is input into a disaster-causing water level inversion model to obtain the probability distribution of disaster-causing water levels. Finally, a flash flood disaster early warning model is constructed, extracting the probability distribution of disaster-causing water levels as model input to perform multi-timescale risk forecasting and classify early warning levels, developing differentiated early warning schemes for different levels. This improves the scientific rigor and effectiveness of flash flood disaster prevention.

The invention discloses a traffic engineering premises mountain torrent risk early warning analysis method based on multi-source perception, and relates to the technical field of mountain torrent disaster monitoring and emergency management, and the method comprises the steps: carrying out the mountain torrent audio feature recognition of sound pressure signals based on a pre-trained AI model, and carrying out the water body form mutation recognition of video streams; in the far-end server, multi-source sensor data and weather forecast data are fused, weights are distributed to the sensors according to the topographic and geological risk levels of the river reach where the sensors are located, and the comprehensive risk score of the upstream river reach is calculated; predicting a flood routing path, a flood routing speed and a flood range based on the upstream comprehensive risk score and a hydraulic model; dynamically planning an optimal escape path according to the prediction result and the real-time acquired position information of the stationed personnel; according to the method, the upstream fusion decision model based on distance attenuation and river reach weight is adopted, so that the downstream station can sense the threat from the upstream early and accurately.

This invention discloses a deep learning-based automatic flash flood identification and real-time early warning system, comprising: a data acquisition and quality control module for acquiring precipitation and topographic data to generate basic observation data; a precipitation correction and fusion module for generating a rasterized precipitation field and uncertainty metric; a watershed topology construction module for filling depressions and connecting depressions in the topographic data to construct the watershed topology; a spatiotemporal feature generation module for aligning the rasterized precipitation field with the watershed topology to obtain a spatiotemporal feature sequence; a depth prediction module for inputting the spatiotemporal feature sequence into a spatiotemporal deep learning model to generate depth prediction results; a hydrodynamic simulation module for setting initial and boundary conditions on an unstructured grid and outputting hydrodynamic simulation results; and a coupling correction and early warning release module for updating predictions and boundaries, generating tiered early warnings, and archiving them. This invention achieves automatic flash flood identification and real-time early warning.

The present disclosure relates to a flash flood disaster refuge transfer path planning method, device and system. The method comprises: obtaining to-be-transferred position information and target transfer position information; determining a to-be-planned path region based on the to-be-transferred position information and the target transfer position information, and taking a node corresponding to the to-be-transferred position information as a starting point and a node corresponding to the target transfer position information as an ending point; performing grid division on the to-be-planned path region to obtain a plurality of grids and a plurality of nodes corresponding to the plurality of grids respectively; the plurality of nodes include the starting point and the ending point; based on an A* algorithm, a preset cost estimation function is used to calculate a cost estimation value of a candidate node in the plurality of nodes; and a planning path is generated by using the cost estimation value of each candidate node, the starting point and the ending point. The present scheme can quickly and accurately complete the planning of the transfer refuge path.

This invention discloses a method for simulating complex slope runoff based on multi-source data fusion. It includes: fusing UAV LiDAR, ground-penetrating radar, and remote sensing images, and considering physical coupling relationships such as vegetation root systems, to generate a high-precision and physically consistent initial surface parameter field; identifying micro-topographic depressions using graph cutting algorithms and constructing a dynamically evolving slope overflow network based on a depression-filling-overflow mechanism; establishing a dynamic feedback control mechanism of overflow-scour-infiltration: the scour intensity calculated based on overflow data is used to correct the soil saturated hydraulic conductivity in real time, and the corrected parameters are then fed back into an improved Green-Ampt infiltration model; and outputting the spatiotemporal distribution of slope runoff through multi-timescale algorithm coupling, which can trigger early warning and invert critical rainfall conditions. This invention can simulate the dynamic feedback process of the underlying surface, improve simulation reliability, and provide technical support for flash flood early warning.

This invention provides a structure for flood control, aiming to address the challenges of impact damage, energy dissipation and deceleration, and smooth transition between mountain flood interception ditches and urban drainage systems. The invention mainly includes a cascading water system, a gradually widening section, an energy dissipation pool, a grating, a retaining wall, a slope toe, connecting pipes, ground level, inspection wells, and an energy dissipation sill. Through a three-stage energy dissipation system (cascading water system + energy dissipation pool + energy dissipation sill), the water flow velocity is significantly reduced. The grating intercepts debris and filters wastewater before it is channeled into the urban pipe network. A liquid level sensor triggers an alarm, providing sufficient emergency response time for wastewater treatment plants. This modular structure is suitable for narrow mountain sites, with a short construction period and high practicality.

This invention provides a dynamic prediction method for flash floods based on satellite remote sensing multi-source data fusion and a spatiotemporal Transformer, including multi-source data acquisition and fusion, feature extraction and dimensionality reduction, model construction and training, and flash flood risk assessment and prediction. This invention deeply integrates advanced data fusion algorithms and a spatiotemporal Transformer network architecture to efficiently process multi-source heterogeneous data such as rainfall distribution, topography, and vegetation cover acquired by satellite remote sensing. The spatiotemporal Transformer network, with its powerful attention mechanism, can accurately capture the coupling relationships and dynamic evolution patterns of various influencing factors in the spatiotemporal dimension during the occurrence and development of flash floods. Compared with existing technologies based on satellite remote sensing and deep learning, this method significantly improves the prediction accuracy of flash floods, providing more reliable data support for disaster early warning and emergency decision-making.

The invention relates to a mountain torrent early warning method and system based on AI cross validation, a terminal and a medium, and relates to the technical field of natural disaster prediction, and the method comprises the steps: responding to the triggering information of mountain torrent early warning, and determining a target rainfall station corresponding to the triggering information; obtaining rainfall data of an associated rainfall station of the target rainfall station; generating a rainfall rechecking result according to the rainfall data; acquiring water level data corresponding to the target rainfall station; generating a water level review result according to the water level data; determining a river video of the target rainfall station; generating a video review result according to the river video; under the condition that the rainfall review result, the water level review result and the video review result all pass review, mountain torrent early warning information is issued; and under the condition that any one of the rainfall review result, the water level review result or the video review result does not pass the review, executing an artificial review process. The method has the effect of reducing the false alarm probability of the mountain torrents.

The present application relates to mountain torrent monitoring technical field, especially to a kind of mountain torrent disaster real-time monitoring method and system fusing radar and video.It includes:through radar equipment and video equipment respectively obtain water flow velocity signal and mountain torrent area image sequence, and through time stamp calibration mechanism alignment acquisition data frequency difference, form preliminary alignment of time and space multi-source data set;From data set extract motion feature vector and boundary contour feature, and filter smooth processing is carried out to motion feature, remove noise;Correct time stamp offset, ensure data time uniformity, and through spatial mapping, motion feature and boundary contour feature are associated, and fusion feature map is generated;Through fusion feature map, the corresponding relationship of water flow velocity and boundary contour is calculated, dynamic hydrological parameter distribution map is generated, high-risk disaster range is marked, and comprehensive monitoring report is generated, and mountain torrent disaster state is determined in real time.The present application effectively improves the real-time monitoring precision and early warning capability of mountain torrent disaster.

The invention relates to the technical field of sudden mountain torrent prediction, and discloses a sudden mountain torrent time early warning method and system based on minute-level runoff simulation, and the method comprises the steps: constructing a fully-distributed mountain torrent runoff confluence model, and outputting a minute-level water depth time sequence of at least one focus point through the fully-distributed mountain torrent runoff confluence model; constructing a sudden mountain torrent index SHI according to physical and hydrological characteristics and statistical characteristics of water depth abrupt change; according to related parameters of historical sudden mountain torrent accidents, calibrating parameters of a fully-distributed mountain torrent runoff confluence model and parameters in a sudden mountain torrent index SHI; each SHI value corresponding to the time sequence in the to-be-predicted range is compared with a preset early warning threshold, when the SHI value corresponding to a certain moment exceeds the early warning threshold, it is judged that sudden mountain torrents are about to occur at the moment corresponding to the concern point, the moment is output as a sudden change point, sudden mountain torrent early warning is carried out, the rainfall time-space precision of simulation is improved, and the rainfall prediction efficiency is improved. And the sudden mountain torrent time early warning is realized.

This invention belongs to the field of data processing technology, specifically relating to a method and system for flash flood disaster early warning based on meteorological and hydrological collaborative analysis. The method includes: acquiring and processing topographic datasets and rainfall data sequences as model inputs for the target early warning area; acquiring multiple topographic geometric parameters for calculating terrain energy; calculating the current terrain energy; accumulating the unit previous impact rainfall, the mean of previous target rainfall across all grid cells, and the standard deviation of previous target rainfall; calculating the current dynamic runoff coefficient; obtaining the current runoff intensity; calculating the current runoff velocity based on the regulatory effect of dynamic hydrological conditions on the static base flow velocity determined solely by topography; and inputting the current runoff velocities of all grid cells within the target early warning area into a distributed hydrological model for early warning. This invention solves the problem that existing distributed hydrological models cannot dynamically reflect differences in runoff generation and runoff changes.

The invention relates to a passive safety system that allows forced filling and water level control inside pressurised or near-pressurised compartments that may be dragged away during flash floods or river floods. The system quickly fills the compartment by force pumping exterior rain water. The increase in the level inside the compartment is controlled, eliminating buoyancy and even allowing an extra load to be applied to the floor if the interior level exceeds the exterior level. The integrity of the compartment is thus ensured while preventing possible collisions with third parties. The exterior water is conditioned to ensure that it enters the compartment clean, facilitating subsequent cleaning and drying.

This invention discloses an automatic regulating drift barrier and its regulating method at the intake of a hydropower station, relating to the field of river pollution control technology. Its main technical solution is as follows: two adjacent drift barrier units are connected by a connector; a driving component is connected to any one of the connectors; a module acquires the theoretical tension force; when the theoretical tension force exceeds the breaking force of the drift barrier body, the control module controls the driving component to disconnect the corresponding two drift barrier units. In extreme conditions (such as heavy rain, flash floods, or flood season), the driving component is preemptively controlled to disconnect the two drift barrier units. This disconnects the drift barrier body into two parts, forming a water flow channel between them. The aim is to reduce the risk of damage to the drift barrier body due to water flow impact, thereby reducing the risk of debris buildup and preventing downstream equipment blockage and mechanical damage caused by debris carried downstream by the water flow.

The invention relates to an effective defense posture formation evaluation method and system for simulating mountain torrents, and belongs to the technical field of simulation devices. The method comprises the steps that the sectional area and flow data of a circulating water tank are obtained, a flood flow model is established, and constant flow velocity analysis is conducted on the flood flow to obtain comprehensive simulation flow; flow path data and flow area of the simulated flood are obtained, a true water environment drilling device is established, and a stress matrix for resisting the flood impact force is calculated; setting a formation for resisting water level burst to obtain a test set, and testing the test set according to the stress matrix to obtain ideal position data; position estimation is carried out on personnel positions of all the formations in the test set through the wireless sensor network to obtain position data, and the effective defense degree of all the formations in the test set is evaluated by calculating distance measurement of the position data and ideal position data. The flood outbreak is simulated, the effective formation defending posture is evaluated, and the correct formation and coping strategy for defending the water level outbreak are mastered.

This invention belongs to the field of flash flood disaster prevention and mitigation, and provides a method for identifying all types of flash flood disasters by coupling hydrodynamics and riverbed morphology. This method analyzes the relationship between upstream and downstream hydrodynamic conditions and riverbed morphology in the river section where the flash flood disaster prevention area is located, constructs a quantitative index reflecting the type of flash flood disaster—the modified riverbed morphology coefficient, and then determines the threshold of the modified riverbed morphology coefficient for different types of flash flood disasters. Based on the modified riverbed morphology coefficient, it achieves the identification of three types of flash flood disasters: flash flood, flash flood-sediment disaster, and flash flood-debris flow disaster. This invention solves the problem that existing technologies can only identify the prone areas of a single type of flash flood disaster, such as flash flood or flash flood-sediment disaster, achieving the identification of all types of flash flood disasters and providing strong technical support for the regional defense of flash flood disasters.

This invention provides a method for preventing flash floods based on flow control, including determining the maximum allowable flow rate of a river section, the maximum allowable discharge flow rate of each tributary, the design flow process of the tributaries, and the method for regulating water volume. Based on the above information, it also presents the design concept for the orifice size of the control dam used in this measure. Compared with the current common method of simply raising the levee standards of urban river sections to resist flash floods, this method only changes the flow process when the flood flow exceeds the design standard, without changing the flow process of the tributaries at other times, thus avoiding long-term inundation; it only requires the construction of the dam body, without the need for gates or other control facilities, resulting in low investment; it eliminates operational scheduling issues, effectively reducing urban flash flood losses and achieving high overall benefits; after the flood, only possible debris such as branches need to be cleared to prevent orifice blockage, resulting in low maintenance costs. This method is beneficial for the development of flash flood prevention work in mountainous towns, enabling more effective resistance to flash floods and prevention of urban flooding.

This invention discloses a method for identifying flash flood and debris flow risks by integrating mechanisms, remote sensing, and deep learning. The method includes a data fusion and standardization module, a mechanism simulation module, a remote sensing identification module, a deep learning module considering physical constraints, and an interpretability analysis and closed-loop decentralization module. By constructing a unified data interface, a unified data model, a physical-data dual-driven system, and a closed-loop self-learning structure, this method achieves deep integration and complementary advantages of the three technologies: mechanism, remote sensing, and deep learning. It effectively solves the technical problems of traditional disaster identification methods, such as data heterogeneity, difficulty in data interoperability, low efficiency, weak model generalization ability, and poor interpretability. It constructs a self-learning and adaptive intelligent risk identification system, thereby improving the accuracy, real-time performance, and practicality of flash flood and debris flow risk identification and assessment, and providing scientific support for risk decision-making by management departments.

The invention discloses a multi-parameter automatic monitoring method and device for rainstorm-induced mountain torrents, and relates to the technical field of mountain torrent disaster monitoring and early warning, and the method comprises the steps: recognizing a rainstorm scene mode of a current region; inputting the parameters into a pre-constructed multi-parameter dynamic monitoring module, selecting a matched monitoring parameter set, and obtaining a matched parameter weight network; acquiring a monitoring parameter sensing data set matched with the monitoring parameter set according to the multi-parameter integrated monitoring module, and performing derivative parameter learning to output a derivative parameter set; and finally, analyzing the weight network, the sensing data and the derivative parameter data to obtain a mountain torrent risk index. The technical problem that the acquired monitoring data is not comprehensive and accurate enough due to the fact that a traditional rainstorm mountain torrent monitoring method is difficult to flexibly adjust the monitoring mode according to the actual rainfall condition and the regional environment is solved, and the purposes of comprehensively acquiring effective monitoring related data, improving the accuracy of mountain torrent risk assessment and improving the reliability of mountain torrent risk assessment are achieved. And the technical effects of accurate assessment and effective management and control of the mountain torrent risk are achieved.

Disclosed is a numerical simulation method for rainfall-induced flash flood and debris flow, including: obtaining, based on a continuum medium mechanics manner coupled with a hydrodynamic model of a three-phase medium of water, coarse particles, and fine particles, data required for the numerical simulation method. The present disclosure is based on a theory of continuum mechanics, which realizes the numerical simulation method for the flash flood and debris flow considering rainfall conditions by a finite difference manner based on the continuum medium mechanics manner coupled with the hydrodynamic model of the three-phase medium of the water, the coarse particles, and the fine particles. The method in the present disclosure is able to simulate formation, movement, and sediment transport processes of the flash flood and debris flow under different rainfall condition.