83 results about "Flood risk assessment" patented technology

The invention relates to the technical field of risk management, in particular to a multi-scale urban rainstorm flood risk assessment method. The method comprises the following steps: acquiring a regional basic data set; performing data preprocessing on the regional basic data set to generate a regional basic preprocessed data set; constructing a rainstorm flood risk assessment index system based on the regional basic preprocessing data set to obtain an urban scale flood assessment index, and performing urban scale rainstorm flood risk assessment to obtain an urban scale rainstorm flood risk assessment result; according to the method, the index information is obtained from the open source data, and the defects that in previous researches, part of index data is poor in spatial precision and long in time are overcome; the multi-scale urban rainstorm flood risk assessment method comprehensively considering the urban scale and the block scale is provided, and the accuracy, scientificity and comprehensiveness of urban rainstorm flood risk assessment can be improved.

The invention discloses a reservoir-lake-river system extreme flood simulation and flood control risk assessment method, system and device and a storage medium, and the method comprises the steps: firstly recognizing a risk source factor of a historical extreme flood event, depicting the spatial distribution uncertainty of the risk source factor through a Vine Copula function, and generating a risk source factor sample through Latin hypercube sampling; then, the samples are reduced based on a Neural Gas algorithm, and a risk source factor scene tree is constructed; generating an extreme flood hygrograph scene by combining historical flood data and adopting a same-multiple-ratio scaling method; and then a joint flood control optimization scheduling model is constructed, flood control risks of the reservoir and the lake are evaluated, and the evaluation effect is analyzed. The system is simple in structure and accurate and stable in risk assessment, fine risk assessment of flood disaster high-incidence areas is facilitated, and theoretical support of extreme flood risk assessment can be provided for areas lacking data.

The invention relates to a high-dimensional statistics and hydrodynamic force coupled flood risk assessment method and system. The method comprises the following steps: acquiring historical observation data covering river flow, tide level and rainfall events; constructing a univariate marginal distribution function; connecting the univariate marginal distribution functions of the river flow, the tide level and the rainfall event, and simulating a joint probability distribution function; coupling the joint probability distribution function with the mechanism model to obtain a probability-mechanism coupling model; inputting the determined joint probability boundary condition into a probability-mechanism coupling model, simulating to obtain composite flood scenes in different return periods, and comparing the composite flood scenes with single variable flood scenes in different return periods; and quantizing the contribution of each variable to the change of the submerging area by using the obtained submerging area and the corresponding rainfall event, river flow and coastal tide level data. According to the method, the defect that traditional single-factor evaluation cannot capture multi-factor interaction is overcome, and the accuracy of flood disaster evaluation is greatly improved.

The invention relates to an infrastructure failure cascade flood disaster risk assessment method, which comprises the following steps of: constructing a traffic transportation network topology model of a research area, acquiring basic attributes of infrastructures in the research area, and constructing a directed graph; constructing an infrastructure system model based on the directed graph in combination with a dependency relationship among basic attributes of the infrastructure; simulating a flood condition in the research area in real time, and judging a failure road section based on a flood simulation result and the traffic transportation network topology model; based on the failed road section, the flood simulation result and the infrastructure system model, evaluating the infrastructure cascade failure condition, and obtaining the failure conditions of all infrastructures; and based on the failure conditions of all the infrastructures, evaluating the service state of the infrastructures during the flood period, and taking the service state as a risk evaluation result. Compared with the prior art, the flood risk assessment method has the advantages of more accurate and deep flood risk assessment and the like.

The invention discloses a flood risk map result data coupling and management method, and relates to the technical field of hydrological information processing and geographic information systems, and the method comprises the following steps: obtaining hydrological data and topographic data required by flood risk assessment, including water level time sequence data, submerging depth data and TIN topographic data, and carrying out standardized conversion on data in different formats, and carrying out unified alignment based on a coordinate reference system. According to the method, the coupling precision of the hydrological data and the topographic data is improved through the adaptive Delaunay triangulation algorithm, and simulation distortion caused by time-space mismatching is avoided; the storage is optimized by adopting a topological optimization GeoJSON data structure, so that the query and management efficiency is improved; gPU acceleration rendering and LOD layering technologies are combined, the real-time visualization capability of flood simulation is improved, and efficient and accurate data support is provided for flood prevention emergency management and water conservancy decision making.

The invention relates to the technical field of satellite hydrological data processing, and particularly discloses a GRACE data super-resolution network space downscaling method fusing geographic information and environmental variables, which comprises the following steps: S1, acquiring original resolution GRACE data and original GLDAS data of a research area, and preprocessing the data; s2, dividing the data obtained by preprocessing in the step S1 into a training set and a test set, and training the GRACE data space downscaling model by using the training set to obtain a trained discriminator and a trained generator; and S3, inputting the GRACE low-resolution data in the test set and the high-resolution environment variable at the moment corresponding to the data into the generator trained in the step S2, and finally obtaining a downscaled high-resolution GRACE image. The method not only can be used for dynamic monitoring of regional scale underground water reserves and flood risk assessment, but also can be expanded and applied to scenes such as agricultural drought monitoring and ecological hydrological process simulation.

The invention discloses a flood risk propagation assessment method, device and equipment and a storage medium, and the method comprises the steps: calculating a flood risk value of each sub-basin in a research region according to an obtained flood risk assessment index variable of the research region; grading the flood risk value to obtain a flood risk grade of each sub-basin in the research area; constructing a Markov chain space-time model; determining a flood risk space-time propagation rule according to the Markov chain space-time model; fitting a flood risk propagation function according to a flood risk space-time propagation rule; according to the flood risk propagation function, the flood control water conservancy project operation information data and the historical flood data, determining a flood risk transfer blocking effect of the flood control water conservancy project; constructing a flood risk space-time propagation network model with a space-time dependency relationship; and according to the flood risk space-time propagation network model, evaluating the research area to obtain a flood risk propagation evaluation result.

The invention relates to the technical field of risk evaluation index systems, in particular to a concrete dam flood risk evaluation index system construction method. The method comprises the following steps: carrying out flow velocity gradient analysis on river channel data of an upstream area of an earth dam to obtain river channel rainy season flow velocity gradient data; performing water depth increment rate calculation on the flow and flow velocity gradient data in the rainy season of the riverway, and performing stratified pressure water flow impact simulation calculation among different water depths to obtain stratified pressure water flow impact data; performing fatigue limit load strength estimation on the concrete dam structure design data according to the layered pressure water flow impact data to obtain fatigue limit load strength estimation data; performing flood risk level prediction on the fatigue limit load intensity estimation data to obtain flood risk level data; and carrying out risk evaluation system construction on the flood risk level data to obtain a flood risk evaluation system. According to the method, the risk evaluation index system technology is optimized, so that the risk evaluation index system technology is more perfect.

The invention relates to the technical field of hydrometeorological monitoring, in particular to a rainstorm flood water line early warning and monitoring method. According to the invention, the consistency and timeliness of real-time water level data from different data sources are ensured through a multi-source hydrometeorological data acquisition and time synchronization technology. Through accurate time synchronization processing, deviation caused by data time lag is avoided, accurate butt joint and fusion of various water level data are guaranteed, and subsequent flood risk assessment and early warning are more reliable. Particularly, under sudden weather conditions such as rainstorm and the like, quick response can be realized, and accurate risk assessment can be provided; according to the method, the noise in the water level data of each data source is effectively removed by combining a combined preprocessing algorithm of moving average filtering and Kalman filtering, and weights of different data sources are weighted according to prediction errors, so that comprehensive accurate water level data is obtained. According to the fusion method, the smoothness and accuracy of the data are improved, and high-quality input data are provided for subsequent risk assessment.

The invention discloses a multi-dimensional flood risk assessment method and system oriented to personnel, traffic and economy. The method comprises the following steps: acquiring multi-source data, and generating flood spatio-temporal evolution data through hydrodynamic simulation; constructing a time-dependent traffic network driven by flood power, wherein the road traffic capacity is dynamically attenuated along with hydrodynamic parameters; on the basis of a space-time racing mechanism, calculating the time difference between the personnel danger arrival time and the shortest evacuation time consumption, and constructing an evacuation time margin and evacuation success probability model so as to dynamically correct the static personnel exposure risk and obtain a personnel safety risk index; and in combination with physical state attenuation and asset exposure characteristics, traffic operation and economic loss risk indexes are calculated respectively, and multi-dimensional fusion evaluation is carried out. According to the method, the problem that dynamic interaction between flood routing and personnel evacuation is neglected in traditional static assessment is solved, accurate calculation of personnel trapped probability and critical road section rush-through marginal contribution is realized, and scientific decision support is provided for flood control command and emergency rescue.

The invention discloses an urban flood mapping and driving factor analysis method based on multi-source remote sensing data, and the method comprises the steps: respectively extracting an optical semi-permanent water body and an SAR semi-permanent water body based on a global surface water body data set and a Sentinel-1 image, and taking the intersection of the optical semi-permanent water body and the SAR semi-permanent water body to generate an enhanced semi-permanent water body mask; extracting a water body in a flood period by using the Sentinel-1 image to obtain flood water body distribution, and performing water body extraction precision verification in combination with the Sentinel-2 image; the precision of the SRTM DEM is improved based on a DEM error prediction model of a Transform network, and a corrected DEM is generated; and constructing a multi-dimensional spatial analysis model based on the elevation, gradient and surface coverage type of the corrected DEM, and identifying spatial distribution characteristics and a terrain driving mechanism of the flood water body. According to the method, comprehensive analysis is performed in combination with terrain factors, and the spatial precision and timeliness of flood risk assessment can be improved.

The invention provides an urban rainstorm flood risk assessment method, system, device and medium, and belongs to the technical field of flood disaster emergency management, and the method comprises the following steps: obtaining social media real-time data of a target urban rainstorm flood event, and constructing different types of data sets; based on the constructed data set, using the trained ViT to screen out rainstorm flood picture real-time data; using the trained DeepLab V < 3 + > to extract a water body object; human and vehicle targets are extracted by using the trained YOLO V8; detecting whether the water body object is overlapped with the human and vehicle targets or not, and if yes, marking the water body object as a danger-related picture; the risk-related positions corresponding to all the risk-related pictures are synchronized to a map, and a thermodynamic diagram is generated; and evaluating the urban rainstorm flood risk area through the thermodynamic diagram. According to the method, the urban rainstorm flood risk area can be accurately evaluated.

The invention provides an urban road network flood risk assessment method based on Bayesian and complex network modeling, and relates to the technical field of flood disaster prevention and reduction. Model parameters are optimized by analyzing and researching spatial heterogeneity distribution of historical flood in a region, and flood susceptibility is predicted based on the optimized Bayesian network model; carrying out modeling analysis on the urban road network topological structure by adopting a complex network theory framework to obtain the road network vulnerability of the research region; and comprehensively scoring the flood risk according to the flood susceptibility and the road network vulnerability, and obtaining the dynamic change of the comprehensive score of the flood risk by adjusting the model and the road network structure. According to the method, the Bayesian network and the Domirank algorithm are combined, the complex causal relationship between each influence factor and the flood disaster is deeply analyzed and quantified, and the capability of coping with the flood disaster of a city can be improved.

The invention provides a flood risk assessment early warning method and system based on big data analysis, and relates to the field of natural disaster risk assessment. The big data analysis-based flood risk assessment and early warning method comprises the following steps of S1, collecting basic information of a regional river through big data; s2, real-time information of a regional river is collected through the Internet of Things; the invention further provides a flood risk assessment early warning system which comprises a big data acquisition module, an online monitoring module, a data processing module, a model construction module, a virtual operation module and a self-learning module. According to the scheme, the water level change condition in a prediction period is finally realized according to the predicted meteorological information, and the prediction, evaluation and early warning of flood risks in an analysis area range are realized; and reliable data support is provided for effective prediction, evaluation and early warning of natural disasters.

The invention relates to the technical field of flood disaster simulation, in particular to a watershed flood dynamic simulation system based on multi-source data fusion, which comprises a multi-source data preprocessing module, a multi-source data fusion module, a digital twin watershed modeling module, a flood dynamic simulation module, a flood risk assessment module and a visualization module. According to the scheme, a space-time cross-modal interaction fusion method is put forward to fuse multi-source data, a cross-modal interaction mechanism is introduced to capture dependency in a modal, high-dimensional interaction tensors are efficiently fused by means of low-rank decomposition, complementarity of space topology, time dynamic and multi-source heterogeneous data is considered, and multi-source data fusion efficiency is improved. The precision and robustness of hydrological process modeling are effectively improved; by constructing a distributed hydrological-hydrodynamic coupling model, whole-process dynamic simulation from runoff production to river channel-flood area flood routing is realized.

The invention belongs to the technical field of flood risk assessment, and particularly relates to a plain water network area standard-exceeding rainstorm risk assessment analysis method, which comprises the following steps: 1, data acquisition: acquiring comprehensive data of a to-be-assessed area, the comprehensive data comprises landform, a hydraulic pipe network, hydrologic catchment, a station gate, a river network, a river channel, an embankment, past rainfall and humanity information; 2, module coupling: according to the acquired comprehensive data, constructing a comprehensive data module of the to-be-evaluated region, and constructing a stereoscopic model of the to-be-evaluated region through the comprehensive data module; 3, verifying the model; 4, simulating rainfall; and 5, outputting a result. By establishing a plurality of data modules, the plurality of data modules are coupled into the region model, and rainfall is simulated through the rainfall module, so that real-time calculation of rainstorm in the assessment region is realized, the real condition of the assessment region is better fit, and the effect of improving the risk assessment accuracy is achieved.

The present invention discloses a basin flood risk assessment method and system based on a particle recognition algorithm, and belongs to the field of flood warning technology. Although the existing scheme can measure the real-time flow of the river, it does not involve how to deduce and evaluate the flood inundation situation, resulting in the inability to quickly know the flood inundation situation around the river bank. The basin flood risk assessment method based on a particle recognition algorithm of the present invention, by constructing a basin spatial discrete model, a flow velocity calculation model, a flow simulation model, a two-dimensional hydrodynamic model, and a flood risk assessment model, can not only calculate the cross-sectional flow of the basin, but also deduce and evaluate the flood inundation situation, so that the flood inundation risk and inundation data around the water area can be quickly known, so as to meet the needs of basin flood risk analysis, improve the accuracy of flood disaster warning, and provide more data supplement and management basis for basin flood control.

The invention discloses a dynamic flood risk evaluation method based on flood inundation simulation, and relates to the technical field of natural disasters. The method includes: acquiring meteorological and hydrological data of a target area; constructing a flood risk model according to the meteorological and hydrological data, and carrying out flood risk model parameter calibration by utilizing actually measured rainfall data and flow-water level data; based on a D8 diffusion algorithm and water balance equivalent analysis of a GIS spatial analysis technology, converting the water amount, higher than the river embankment, of the target area into a submerged water depth sum by using the constructed flood risk model, obtaining a submerged water depth map of the target area, and generating a flood deduction result; and according to the flood deduction result, determining flood disaster risk grade division of the target area, and evaluating the flood disaster risk. According to the method, the flood risk model and the flood rehearsal model of GIS spatial analysis are constructed, and the flood risk model can well reflect the flood rehearsal result.

The invention discloses an urban water flooding risk early warning method based on radar and ground precipitation fusion. The method comprises the steps of terrain analysis and calculation; analyzing a waterlogging area and flooding grid filling, and generating a flooding area watershed topology; rainfall station monitoring data and radar echo map data are integrated, and rainfall forecast grids are integrated; rainfall fusion interpolation is carried out based on actually measured rainfall of a rainfall station and a radar echo map; matching a rainfall grid; extracting an average rainfall sequence of all flooding basin surfaces; extracting an average rainfall sequence of the sub-basin units from the forecast rainfall source; loading and analyzing an input file, constructing an internal data structure and creating a result output grid template; calculating rainfall flooding; performing flooding risk assessment and early warning display; the problems that in the prior art, data information needed in urban water accumulation risk early warning analysis is numerous, and particularly, the accurate acquisition difficulty of urban drainage pipe network data is large are solved; the problem that urban rainstorm intensity and rainstorm volume space distribution cannot be accurately reflected in the prior art is solved.

The invention discloses a night flood scene water level grade automatic estimation method based on a bus wading image and an improved YOLOv8 algorithm. The method comprises the specific steps that a receipt library is acquired; the collected data is preprocessed; a picture data enhancement strategy is adopted for the night flood scene images meeting the requirements; labeling all the images by using Label and storing the images as a YOLO format file; a proper YOLOv8 model is selected for improvement and optimization; setting reasonable training parameters, and training the constructed comprehensive data set by using the improved grid structure; and performing urban flood water level identification estimation by using the trained optimal weight file. By means of social media big data and the improved YOLOv8 algorithm, low-cost, rapid-detection and high-accuracy urban flood water level automatic estimation is achieved, meanwhile, the detection performance of the model in a night scene is improved, and reliable technical support is provided for real-time flood risk assessment and emergency management of a night urban traffic system; the important application potential is realized.

The invention provides a multi-source data fusion flood risk assessment early warning method, and relates to the technical field of natural disaster early warning. The multi-source data fusion flood risk assessment early warning method comprises the following steps: data acquisition: acquiring meteorological data including but not limited to rainfall, air temperature, air pressure and wind speed; hydrological data including river flow, water level and soil humidity are collected; collecting geographic data including terrain elevation, land utilization type and vegetation coverage; social data including population density, building distribution and infrastructure conditions are collected; and data preprocessing: cleaning the collected data, removing noise and abnormal values, and carrying out standardization processing on the data to ensure that the data of different data sources has comparability. According to the flood risk assessment method, multi-dimensional features of flood risks can be comprehensively reflected by integrating multi-source data of meteorology, hydrology, geography, society and the like, and richer information support is provided by integrating different types of data, so that risk assessment is more comprehensive and accurate.

The invention provides a flood risk management method and system, a computer and a storage medium, and the method comprises the following steps: carrying out the numerical modeling based on ground surface features through employing a digital twin technology, and building a hydrodynamic model based on a shallow water equation; monitoring and obtaining flood risk data of each region; the operation scheme of the hydraulic structure is optimized based on the flood risk data, the hydrodynamic model is transferred, the water network flow evolution process of the optimized operation scheme of the hydraulic structure is simulated, and the water network is monitored and managed. Through combination of the hydrodynamic model and flood risk assessment, when the flood risk is found, an intelligent optimization algorithm can be automatically called to dispatch gates, dams and other hydraulic structures, the flood risk is coped with in real time, the influence of potential disasters is reduced, compared with traditional manual dispatching, delay or misjudgment caused by human intervention can be reduced, and the working efficiency is improved. And the flood control scheduling efficiency and accuracy are improved.

The invention discloses an electric power gallery flood risk assessment method and system based on deep learning, and belongs to the field of flood disasters, and the method comprises the steps: achieving the water extraction and risk grade assessment of a radar image, obtaining the radar image from a Sentinel-1 satellite, removing the noise through a Speckle filter, and carrying out the geometric correction, radiation correction and normalization processing. Data preprocessing is carried out to ensure data quality; performing image segmentation on the preprocessed image by using a U-Net model, extracting and recovering image features through an encoder and decoder structure, and realizing high-precision water body segmentation through a deep learning model; the water body extraction precision is evaluated by calculating indexes such as a confusion matrix, a recall rate, accuracy and MIOU, the flood risk level of the power equipment is evaluated according to the extracted water body data, the gallery bridge distance and the gradient, and risk evaluation is divided into five levels. According to the method, the problem of how to accurately extract the water body and evaluate the flood risk of the electric power gallery is solved, and a scientific basis is provided for protection and management of electric power facilities.

This invention relates to an airport rainfall and flood early warning method, electronic device, and medium based on a large language model, for use in sponge airports. The early warning method includes: based on a rainstorm and flood management model, using a large language model for data augmentation to generate a multi-factor flood early warning dataset containing regionally specific factor data and airport-specific factor data; based on a retrieval-enhanced generation mechanism, vectorizing and calculating feature bias on the current input data, retrieving the most relevant historical case context information from the multi-factor flood early warning dataset; adaptively fusing the multi-factor features and the most relevant historical case context information, extracting key information through multi-head self-attention and attention pooling, and outputting the flood risk level and early warning result. This invention can significantly improve the accuracy, real-time performance, and interpretability of flood risk assessment, providing more reliable, traceable, and intelligent flood early warning and decision support for sponge airports.

The invention relates to the technical field of urban rainfall pattern recognition, and aims to solve the problems that an existing method depends on an empirical formula, rainfall classification is unstable, and interpretability is insufficient. The method comprises the following steps: acquiring multi-site long-time actually measured rainfall data, and identifying an independent rainfall event based on a rainfall interval threshold value; multi-dimensional features such as rainfall duration and peak rainfall intensity are extracted and standardized; performing hierarchical clustering by adopting a Ward minimum variance method, and determining an optimal clustering number by combining a Clinski-Harabasz index and the like to obtain a rainfall mode; training a linear discriminant analysis (LDA) model by taking a clustering result as a label, and verifying and quickly classifying a new rainfall event; the result is used for flood control scheduling, flood risk assessment and the like. According to the method, rationality is improved based on measured data, classification stability is improved by fusing clustering and discriminant analysis, expandability is high, and intelligent disaster prevention is supported.

This application provides a method, apparatus, equipment, and storage medium for assessing drought / flood disaster risks in tobacco cultivation. It relates to the field of hydrological technology. The method includes: analyzing the response relationship between drought / flood conditions and actual disasters in different months of the tobacco growing season based on multi-timescale SPI analysis; calculating the distribution sequence of drought / flood conditions with a high probability of causing drought / flood disasters using the Naive Bayes method; constructing a new paradigm for assessing the risk of drought and flood disasters during the tobacco growing season based on drought / flood type classification, Bayesian modeling, and disaster-causing effect quantification; and further establishing a three-dimensional simplified framework drought / flood risk assessment model. This application aims to establish a drought / flood risk assessment model by analyzing the response relationship between drought / flood conditions and actual disasters in different months of the tobacco growing season based on multi-timescale SPI analysis, calculating the distribution sequence of drought / flood conditions with a high probability of causing drought / flood disasters using the Naive Bayes method, and then establishing a drought / flood risk assessment model.

The invention relates to a flood risk assessment method and system based on cavernous body benefits. The method comprises the following steps: acquiring real-time data; performing multiple fusion on the data to form standardized rainfall, drainage system state, cavernous body basic parameters and terrain exposure; calculating cavernous body regulation and storage benefits based on the cavernous body basic parameters; obtaining a comprehensive risk index based on the rainfall, the drainage system state, the terrain exposure degree and the cavernous body regulation and storage benefit; and on the basis of the comprehensive risk index, with the purpose of minimizing the comprehensive cost, generating an optimal scheduling scheme of the drainage system in combination with a zoning and grading scheduling method and a linear programming and heuristic optimization algorithm. According to the method, multi-source data real-time closed-loop fusion and dynamic regulation and storage function cooperation are innovatively introduced, so that data space-time integrity and continuity are guaranteed, actual benefits of the cavernous body can be quantified, and full-chain management and control are formed; an integrated closed-loop framework of closed-loop control risk index and scheduling optimization of risk perception, risk assessment and intelligent scheduling is realized for the first time.

The invention relates to a flood collaborative forecast management system and method based on big data analysis, and belongs to the technical field of big data analysis. The method comprises the steps that a grid gradient set of a target monitoring drainage basin is obtained according to overlook topographic data, a sub-drainage basin grid set and a sub-drainage basin set are obtained according to the grid gradient set, and sub-drainage basin division can help to improve the accuracy of flood dam burst position positioning of the target monitoring drainage basin; the method comprises the following steps: constructing a sub-basin topographic parameter set according to a sub-basin set, carrying out feature extraction on the sub-basin topographic parameter set to obtain a sub-basin topographic feature set, and analyzing the sub-basin topographic feature set to obtain referable flood data, thereby solving the problem of scarcity of target monitoring basin data, improving the reference of the data, and improving the accuracy of flood monitoring. The flood risk assessment model is used to process the referable flood data and the real-time monitoring data set to obtain the flood risk coefficient, and the flood forecasting list is obtained according to the flood risk coefficient, so that the management efficiency of flood forecasting is improved.

The present invention discloses a method for quantitatively evaluating real-time flood risk. The method establishes the relationship between flood frequency (P), corresponding loss (L), and flood control risk rate (P f ), and constructs a flood risk control standard diagram, thereby quantitatively evaluating the risk level of real-time flood, that is, determining whether it belongs to the acceptable risk area, the tolerable risk area, or the unacceptable risk area. The solution provided by the present invention for quantitatively evaluating real-time flood risk overcomes the deficiency in the current hydrological field that the risk control standard for real-time flood risk assessment only considers the flood control risk rate or flood occurrence frequency without considering flood losses. By combining the flood control risk rate and flood losses, the risk control standard can be tailored to specific situations and adapt to different flood control protection objects, providing a technical basis for basin flood control, disaster reduction, and emergency management.

The invention relates to the technical field of mountain torrent flood control and disaster reduction, and discloses a small watershed mountain torrent risk assessment method and device, electronic equipment and a storage medium. Establishing a spatial association relationship between each danger area and the rainfall monitoring station based on the spatial association relationship between the small watershed and the danger area; based on the spatial association relationship between each danger area and the rainfall monitoring station, calculating the preset accumulated rainfall in each time period of each danger area in a rolling manner; and based on the relationship between the accumulated rainfall capacity of each preset time period of each danger area and the rainfall early warning threshold value of each preset time period, evaluating the small watershed mountain torrent risk. According to the method, a'small watershed-dangerous area-monitoring station 'space correlation system is established, refined description of rainfall spatial and temporal distribution and regional difference is realized, and a set of systematic and automatic mountain torrent risk assessment method is constructed by means of multi-period rolling accumulation calculation and dynamic threshold comparison.