69 results about "Flood water" patented technology

The invention discloses an attention-based deep learning urban flood affected population evaluation method and system, and the method comprises the following steps: collecting rainfall, flood water depth, terrain, pipe network and satellite image data of a research region, carrying out the preprocessing, and constructing a first data set and a second data set; and training and verifying the first deep learning model and the second deep learning model respectively. Inputting the first data set test set into the first model, and outputting a flood water depth prediction map; and inputting the second data set test set into the second model, and outputting a land utilization segmentation map. The two maps are superposed to obtain matching data of the flood water depth and the land utilization category, the number of exposed people is calculated by adopting an exposed population formula after land utilization reassignment, the population disaster rate is calculated by utilizing a preset flood disaster loss curve in the flood water depth, the number of exposed people and the population disaster rate are multiplied to obtain the number of affected people, and the number of affected people is calculated. And completing urban flood disaster population evaluation. According to the scheme, the accuracy, the reliability and the effectiveness of urban flood disaster population evaluation can be remarkably improved.

The present invention discloses a flooding water level monitoring method and system for power facilities, including after receiving a flooding emergency response notification and a heavy rainfall defense alarm, starting facility flooding water level monitoring; and based on the individual area and total area of facilities affected by flooding and water level sensing monitoring information, establishing a neural network measuring an affected range, and outputting the monitoring result of a flooded surface height in a region, thereby achieving all-weather real-time monitoring, and accurately measuring and timely reporting a flooding height.

The invention discloses a method and a system for determining a forecast flood inundation range, electronic equipment and a storage medium. According to the scheme, geographic basic information data, a basic inundation data result set, a target characteristic section and corresponding forecast flow data of a river channel of a river area are acquired; determining a water level and flow relation curve according to the target characteristic section and the basic inundation data result set, combining the water level and flow relation curve with forecast flow data to carry out calculation processing, determining a forecast flood water surface line, and combining the forecast flood water surface line with geographic basic information data to carry out calculation to obtain a flood inundation range; the forecast flood water surface line data of the whole river is calculated through the target characteristic section in the river area and historical data, so that the calculation processing data is reduced, and the calculation efficiency is improved; historical data and river geographic data are combined to calculate a flood inundation range, the precision of a calculation result is improved, and the application range is expanded; the embodiment of the invention can be widely applied to the technical field of flood inundation range extraction.

The invention relates to the field of urban flood prediction, and discloses an urban time sequence flood rapid prediction method based on a Swin Transform and a hydrological hydrodynamic model, and the method comprises the following steps: obtaining multi-source data of a target region, carrying out the preprocessing, and generating a standardized data set; constructing a flood simulation model based on the hydrological hydrodynamic model, and generating time sequence flood ponding depth data; designing multiple groups of rain pattern data, and driving the flood simulation model to generate diversified flood scenes; constructing a flood prediction model based on Swi n Transform, and training the model by using the flood scene data; and reasoning real-time rainfall data based on the flood prediction model, and outputting a dynamic flood prediction result. According to the method, through advantage complementation of the physical model and deep learning, the calculation efficiency is remarkably improved while the prediction precision is guaranteed, and efficient and reliable technical support is provided for urban flood control emergency and planning.

The invention discloses a method and a system for simulating personnel evacuation under the flood spreading situation of an underground scene, and the method comprises the steps: building an underground scene model, simulating the flood spreading process of the underground scene model, obtaining the flood dynamic information of each position point in the underground scene model, and carrying out the simulation of the flood spreading process of the underground scene model; the flood dynamic information comprises flood water depth, flow velocity and flow direction; gridding the space in the underground scene model, and determining an initial pedestrian position; building a static field, a water depth field, a support field and a flow velocity field based on the cellular automaton, and further calculating the transition probability of pedestrians; judging the human body stability of the pedestrian based on the flood dynamic information, and calculating the moving speed of the pedestrian; and updating the pedestrian position based on the transition probability and the pedestrian moving speed, and finely simulating the evacuation of the pedestrian in the underground scene in the flood spreading process. According to the invention, the movement stability and movement speed of pedestrians in flood are considered, which is beneficial for studying how to evacuate crowds timely, efficiently and safely under the flood situation.

The invention provides a flood simulation method driven by physical and data fusion, and belongs to the technical field of flood simulation, the method comprises the following steps: pre-training to obtain a qualified urban flood simulation model, a target loss function comprising a data supervision loss item and a physical constraint loss item, the physical constraint loss item is composed of a mass conservation residual error loss item, a momentum conservation residual error loss item and an energy conservation residual error loss item; inputting ground elevation data and historical meteorological data of a target area in a city into the hydrological model to obtain water depth grid data and flow velocity grid data, and inputting the water depth grid data and the flow velocity grid data into the city flood simulation model for prediction processing to obtain water depth grid data and flow velocity grid data of the target area at different time points in the future; and based on the data at different time points, generating an urban flood ponding dynamic evolution graph of the target area. The invention aims to improve the efficiency and accuracy of urban flood scene prediction.

The invention discloses a simulation method for urban flood emergency rescue path planning, and the method comprises the steps: carrying out the modeling of an urban road network based on an urban topographic map, rainfall data, existing water distribution and key position information; mIKE simulation software is used for establishing a hydrodynamic model to simulate the rainfall and flood spreading process of the city, and flood dynamic information, including the depth and flow velocity of the flood, at each position point in the flood disaster scene model is obtained; respectively constructing objective functions according to the shortest maximum time of arrival of the disaster relief point, the lowest driving risk of the rescue vehicle and the shortest total weighted rescue time; setting constraint conditions to ensure that all disaster relief points are covered, and preventing vehicles from being excessively distributed; based on the flood dynamic information, the objective function and the constraint condition, adopting an NSGA-II non-dominated sorting genetic algorithm to solve a Pareto solution set; and performing weighted analysis on a result in the Pareto solution set to obtain an optimal solution, and outputting an urban flood emergency rescue path plan.

The invention discloses a water level time sequence data cleaning method based on regression statistics, which comprises the following steps: S1, sorting flood data of a historical session of a monitoring station to form a complete flood sample set; s2, establishing a function model according to the nonlinear change characteristics of the flood water level; s3, performing regression function fitting on the historical flood sample data, and calculating linear correlation between each fitting function and actual data; s4, based on a fitting result of the optimal regression function, establishing a Gaussian distribution model of a difference value; s5, determining a confidence interval of Gaussian distribution through the verification sample, and judging whether the data is abnormal data or not according to the confidence interval; s6, the detected abnormal data are corrected, and the cleaned data are obtained; and S7, processing the first N time sequence points in the flood time sequence data by adopting a moving average algorithm, and eliminating the interference of accidental fluctuation on regression fitting. The method has the advantages of being high in cleaning precision, high in adaptability and good in flood nonlinear change characteristic processing effect.

The invention discloses a flood emergency strategy generation method and device of a power grid and electronic equipment. The method comprises the steps that initial road data are acquired in a target area of a power grid, and the initial road data are used for representing structural attributes of a road; inputting the initial road data into a road traffic model of a power grid for analysis to obtain an initial traffic result of the road, the road traffic model being obtained by training based on historical road data in the target area, and the initial traffic result being used for representing a predicted traffic condition of the road; determining a target passing result of the road based on the initial passing result and weather forecast information and topographic information in the target area; and generating a flood emergency strategy of the power grid based on the attribute information of the hardware equipment in the target area, the flood depth data in the target area and the target passing result. According to the invention, the technical problems of slow generation speed and low timeliness of the flood emergency strategy are solved.

The invention relates to the technical field of flood disaster prevention, in particular to a flood homing calculation method and simulation system based on overflow process correction. The method comprises the following steps: collecting and processing topographic data of a flood overtopping area to obtain topographic feature parameters; historical flood actual measurement data of the overtopping beach are collected, and the river channel actual measurement flood water level and flow process is obtained; according to the topographic feature parameters and the actually measured flood level process of the river channel, simulating the out-of-groove and in-groove flood processes according to the water balance principle to obtain a simulated flood overtopping flow process; and according to the flood overtopping flow process, groove returning correction is carried out on the actually-measured flood flow process of the river channel to obtain the groove-returning flood flow process of the river channel, and the groove returning flood flow process is used as the basis of groove returning flood design. By simulating the flood beach overflowing process, groove returning correction of the river flood process is achieved, the data requirement is low, flood elements are complete, and operability is high.

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 belongs to the crossing field of water conservancy and computer vision, and provides an urban flood depth real-time monitoring method based on intelligent three-dimensional vision. According to the method, firstly, an unmanned aerial vehicle is adopted for aerial photography to collect multi-view images of scenery in an urban area, and refined three-dimensional reconstruction is carried out on the multi-view images; then, shooting a two-dimensional image of the scenery by using a camera, matching the two-dimensional image with the image shot by the unmanned aerial vehicle, and screening out a plurality of most similar images; dense feature comparison is carried out on the two-dimensional image and the three-dimensional information, and the pose of the camera is calculated according to the corresponding relation of feature points; and finally, through SAM2 segmentation and autoregressive mechanism optimization, extracting a water surface area with a stable time sequence, and in combination with a known camera pose, back-projecting a water surface edge to a three-dimensional space, obtaining the water depth of accumulated water around the scene, and realizing real-time monitoring of urban flood water depth data. The method provides important technical support for fine real-time early warning of urban flood, and has practical engineering application value.

The invention discloses a flood water depth estimation method based on deep learning and an FwDET model. The method is used for solving the problems that in a traditional method, multi-source data consistency is poor, change detection precision is low, water depth estimation is complex, and a structured result is lacked. According to the method, high-precision flood recognition is achieved through double-time-phase same-source SAR remote sensing images, the depth of the flood is rapidly estimated in combination with DEM data, an automatic processing flow is constructed, efficient, accurate and extensible flood disaster monitoring is achieved from pixel-level recognition to vectorization expression, and reliable data support is provided for disaster assessment and emergency response.

The invention discloses a flood water intelligent identification method based on an improved deep learning model, and belongs to the technical field of geological disaster information processing, and the method comprises the following steps: collecting and preprocessing data, and generating a data set; based on the generated data set, integrating Canny edge detection operator texture, normalized water body index texture and local binary pattern (LBP) operator texture to form a multi-feature fusion image data set; a DeepWFNet network model is constructed; inputting the multi-feature fusion image data set into a DeepWFNet network model for flood inundation range identification to obtain a flood identification result; and carrying out visual optimization and evaluation on the flood identification result. According to the method, the edge features, the spectral features and the texture features are added to be combined with the DeepWFNet model, the ability of the model to understand global information can be enhanced while the ability of local feature extraction is kept, and therefore the segmentation precision of the flood inundation area is remarkably improved.

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 present invention relates to the technical field of flood disaster prevention, and particularly relates to a flood channeling calculation method and simulation system based on overflow process correction. The method includes the following steps: collecting and processing topographic data of the floodplain area to obtain topographic characteristic parameters; collecting historical flood measured data of the floodplain to obtain the measured flood water level and flow process of the river channel; simulating the out-of-channel and in-channel flood processes according to the topographic characteristic parameters and the measured flood water level process of the river channel based on the principle of water balance to obtain the simulated floodplain flow process; correcting the measured flood flow process of the river channel according to the floodplain flow process to obtain the channeled flood flow process of the river channel, and using this process as the basis for the design of channeled flood. The present invention realizes the channeling correction of the river channel flood process by simulating the floodplain process, requires less data, has complete flood elements, and is highly operable.

The invention provides a reservoir flood prevention water level early warning method and system and a storage medium, and relates to the technical field of flood prevention water level early warning. Setting a dam judgment rule, selecting historical dam forming data and historical dam breach data from historical data based on the rule, constructing and training a dam breach prediction model based on the data, and obtaining predicted dam breach data through the dam breach prediction model; acquiring water level data and section data of each main branch at the inlet of the reservoir, and determining a dam breaking water level of each main branch at the inlet of the reservoir by combining the current dam existence time and the predicted dam breaking data; and acquiring water level data of the reservoir, combining the water level data of each main branch at the inlet of the reservoir and the dam breaking water level to finish flood prevention grading early warning of the reservoir, and sending out a corresponding early warning signal.

The invention discloses a directional dredging method for silted silt on one side of a river channel. The method comprises the steps that in the pretreatment stage, a longitudinal main groove and a plurality of transverse auxiliary grooves are excavated in a siltation area along water flow, a spur dike is arranged at the initial section of the main groove, and a movable track system carrying a high-pressure erosion and siltation and negative-pressure guide and drainage module is laid along a siltation bank; in the dynamic desilting stage, desilting equipment and reservoir desilting facilities are cooperatively operated according to the hydrological sediment situation in the flood season, all modules and desilting bottom holes are opened in the early stage of flood, the high-pressure desilting module is closed in the middle stage of flood, full-force desilting of the negative-pressure guiding and dredging module is maintained, and the desilting equipment is closed in the last stage of flood, and the discharged flow is gradually reduced; and in the later-stage protection stage, a floating body system with sand blocking and flow guiding functions is arranged on the upstream of the desilting section. According to the method, precise and efficient removal of silted silt on one side is achieved, ecological disturbance is small, and the re-silting speed after desilting can be effectively reduced.

In an approach for efficient flood water analysis from spatio-temporal data fusion and statistics, a processor classifies regular waters by using cartographic data in a first location. A processor generates a water stream network including a watershed based on elevation data. A processor performs statistical analysis of spectral information from a multi-spectral satellite imagery over water bodies including the regular waters and flood waters. A processor correlates the spectral statistics of the multi-spectral satellite imagery to kinetic energy of the flood waters using machine learning techniques and physical modeling. A processor builds a learning model based on the correlation between the spectral statistics and the flood waters with the kinetic energy. A processor estimates kinetic energy of flood waters in a second location using the learning model. A processor evaluates a flooding risk for the second location based on the estimated flood waters kinetic energy.

The invention discloses an urban deep tunnel system integrating rainfall flood water storage and a pumped storage power station, and relates to the technical field of urban drainage waterlogging prevention and energy storage. An urban deep tunnel system integrating rainfall flood storage and a pumped storage power station comprises an urban deep tunnel drainage device, a water storage device, a power generation device and a water delivery device, one end of the urban deep tunnel drainage device is connected to the ground surface, and the other end of the urban deep tunnel drainage device is sequentially connected to the water storage device, the power generation device and the water delivery device. The urban deep tunnels are comprehensively utilized for rainfall flood storage, rainstorm flood is converted into water resources capable of being recycled, the pumped storage power station is introduced, the comprehensive utilization system for preventing and treating urban inland inundation and generating power is developed, the purposes of rainfall flood management and peak regulation and frequency modulation energy storage and power generation are achieved, and high economic benefits are achieved; pollutant emission caused by thermal power and the like in cities is reduced, energy conservation, emission reduction and ecological environment protection of the cities are assisted, and urban inland inundation prevention and treatment are considered.

The present application provides a water stop plate capable of being easily installed and constructing a water stop wall in a short time at any place such as a road, an opening of a building, or the like where flood water enters or is expected to enter. The water stop plate of the present application is a water stop plate (A) capable of constructing a water stop wall by being connected in the left-right direction via a connecting member (B), the water stop plate (A) including a water stop plate main body (A2) and a connecting portion, the water stop plate main body (A2) including a bottom portion (1) placed on a water stop wall construction surface (E) of a water stop wall (F) to be constructed, and an upright portion (2) vertically provided upward from a rear portion of the bottom portion (1), the connecting portion including an upper connecting portion formed on an upper portion of the water stop plate main body (A2) and detachably connected to an upper portion of the connecting member (B), and a lower connecting portion formed on a lower portion of the water stop plate main body (A2) and detachably connected to a lower portion of the connecting member (B).

This invention discloses an intelligent water quality prediction method for watershed floods based on dynamic weight optimization and deep reinforcement learning. The method comprises the following steps: collecting historical flood water quality observation data and historical flood hydrological data; standardizing the historical flood hydrological data to obtain comparison sequences and reference sequences, and then performing dimensionless processing; calculating dynamic grey relational coefficients and weighted grey relational degrees using the dimensionless comparison sequences and reference sequences, and sorting them to form a weighted grey relational degree sequence; using the weighted grey relational degree sequence to filter out effective historical flood fields, and performing dynamic weight optimization based on a long short-term memory network and a reinforcement learning agent based on the TD3 algorithm; and calculating the final predicted flood water quality data using the historical flood water quality observation data and the historical flood weights. This invention's prediction method enables intelligent water quality detection during flood processes, providing accuracy, real-time performance, and adaptability.

The present invention relates to the field of bridge engineering technology, specifically to a probabilistic failure assessment method and system for floating objects hitting bridges during flood season, the method comprising the following steps: collecting floating object data and river hydrological information during flood season and obtaining water flow velocity and floating object movement conditions; establishing a floating object drag force prediction model according to the water flow velocity and floating object movement conditions and analyzing the drag force generated by flood on floating objects based on the model; setting a bridge damage assessment mechanism based on the floating object data during flood season and river hydrological information, and obtaining assessment parameter analysis results based on the assessment mechanism; establishing a probabilistic failure judgment model, combining the drag force, assessment parameter analysis results and the floating object data during flood season and river hydrological information to obtain probabilistic failure assessment results, and realizing risk prediction and assessment of floating objects hitting bridges during flood season. By analyzing the failure mechanism of floating objects hitting bridges, the risk degree of bridge damage under different water flow conditions and floating object characteristics is quantified.

The utility model relates to the technical field of water level surveying, and discloses a flood water level surveying device which comprises an installation shell, a water level gauge is fixedly installed on the surface of the installation shell, a guide opening is formed in the installation shell, a surveying assembly is arranged in the guide opening, and a fixing plate is fixedly installed at the top of the installation shell. A positioning assembly is fixedly installed on the top of the fixing plate, and a traction rope is arranged between the surveying assembly and the positioning assembly. The defects in the prior art are overcome, a worker can place the floating ball at one end of the pulling rope into the guide opening from the top of the mounting shell, the floating ball floats on the water surface, the pulling rope is pressed and fixed through the positioning plate of the positioning assembly, and when the water surface of river water rises, the floating ball vertically rises upwards along with the water surface, so that the floating ball can float on the water surface. Therefore, the rising amount of the water level can be remotely and rapidly known, great convenience is brought to water level surveying work, workers can obtain data and send notifications in real time, and the safety of surrounding residents is further guaranteed.

The present invention discloses a method and system for quickly calculating flood depth based on multi-layer grid overlay analysis, and belongs to the technical field of flood risk analysis. The method includes constructing a meteorological grid, a catchment area grid, and a hydrodynamic model grid; using the intersection area between the meteorological grid and the catchment area grid as the allocation weight, and obtaining real-time rainfall data to calculate the rainfall allocated on the catchment area unit; using the overlay relationship between the catchment area grid and the hydrodynamic model grid and the rainfall allocated on the catchment area unit, the maximum flood depth of the hydrodynamic model grid unit is calculated. The present invention combines distributed databases and parallel computing technology, and proposes an interpolation method based on static-dynamic variable decoupling, which provides results that are relatively consistent with professional models in a short time; through the organic combination of overlay analysis, distributed databases, and parallel computing, not only the accurate calculation of complex data analysis and simulation is achieved, but also the ability to respond quickly is ensured.

The present invention discloses a method for predicting flood inundation areas based on land survey data, and relates to the technical field of flood inundation area prediction. When the dam breach risk coefficient of a target dam is not less than a preset dam breach risk coefficient, a plurality of preliminary inundation sub-areas are simulated according to the flood water flow, and the first flood water storage capacity of each preliminary inundation sub-area is obtained; and the current vegetation density, groundwater level and soil permeability coefficient of each preliminary inundation sub-area are used as a data set, and the data set is clustered to determine the water storage capacity impact index of each preliminary inundation sub-area; a second flood water storage capacity is obtained according to the water storage capacity impact index and the first flood water storage capacity, and a final flood inundation area is determined according to the second flood water storage capacity. In this way, the flood inundation area of ​​the future cycle can be predicted, and the normality of flood control planning and emergency plans can be ensured, so that effective prevention and evacuation can be carried out before the flood comes, and casualties and property losses can be reduced.

The invention discloses a flood protection control method and system for a photovoltaic tracking assembly. The method comprises the following steps: collecting a real-time flood water level; judging whether the real-time flood level is greater than or equal to a flood level threshold; if yes, real-time flood intervention time is collected, whether the real-time flood intervention time is larger than or equal to a flood intervention time threshold value or not is judged, if yes, a first protection instruction is generated to execute flood protection operation, the real-time flood water level is continuously collected, and if the current real-time flood water level is smaller than'flood water level threshold value-threshold fluctuation value ', real-time flood intervention quitting time is collected; and judging whether the time is greater than or equal to the flood exit intervention time threshold, and if so, stopping executing the flood protection operation. The method solves the problem that in an existing photovoltaic tracking support flood control method, only the flood level serves as the judgment basis of protection triggering, and the stability of the duration time of the flood level is not considered.

1. The name of the design product: flood water level monitoring equipment. 2. The use of the design product: a flood water level monitoring equipment. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The present invention provides a base for a flood defence barrier, wherein the base comprises a bottom face intended to rest on the surface on which the base is to be placed, a front face intended to contact the flood water and a rear face on the opposite side of the base to the front face, wherein the front face is positioned at an acute angle to the bottom face, one or more holes extending through the base from the front face to the rear face, and a filtering means on the front face that at least partially covers the one or more holes.

The invention provides a flood water body recognition method, system and device and a storage medium, and belongs to the technical field of flood recognition, and the method comprises the steps: obtaining GRD image data of a target region within a set time period; acquiring a time sequence of grid points for the GRD image data pixel by pixel, and inputting the time sequence into the harmonic regression model to obtain predicted values of pixel points; performing abnormal image recognition according to a difference value between the observed value and the predicted value to obtain a binary flood abnormal image set corresponding to all the GRD images; and counting the precipitation amount of each abnormal flood image in the binary abnormal flood image set in a set time period before and after the set time period, comparing the precipitation amount with the average accumulated precipitation amount in the same time period, and retaining an area exceeding the average accumulated precipitation amount in the abnormal flood images to obtain a flood water body identification result of the target area. The stable identification of flood water bodies in different regional environments is realized, and the identification precision is high.