18 results about "River ice" patented technology

The invention discloses a cold region land surface process river water and sediment model construction method, which comprises the following steps: selecting a target research drainage basin, extracting a drainage basin range ROI (Region of Interest), and collecting water and sediment data and related basic data in the drainage basin range; calculating a thermal erosion amount caused by temperature rise in the river reach, a snow melting erosion amount caused by snow melting, a water erosion amount induced by rainfall and a river ice erosion amount caused by ice running or flow ice scraping erosion of river ice in winter and spring; selecting landform characteristic parameters according to a river flow direction to construct a sediment transport coefficient of a river reach, establishing a cold region river water and sediment model according to the sediment transport coefficient and each erosion source item, and obtaining a sediment content simulation result based on the established cold region river water and sediment model; and evaluating the simulation performance of the model based on the established evaluation index. The method can dynamically respond to the erosion sand production and runoff sand transportation process of the cold region, provides timely and high-precision sand content calculation, and has important significance on water and soil conservation management and water and sand risk regulation and control of the cold region.

The invention discloses a deep learning river ice extraction method based on an optical and SAR fusion image, and belongs to the technical field of remote sensing geoscience application. The method comprises the following steps: acquiring an optical image and an SAR image which are in the same area and contain river ice distribution, preprocessing the optical image and the SAR image, marking river ice areas of the preprocessed optical image and the preprocessed SAR image, and constructing a training data set; a deep learning extraction model is constructed, and the training data set is used for training; and obtaining an optical image and an SAR image of a to-be-extracted river ice distribution region, obtaining a binary image by using the trained deep learning extraction model, converting the binary image into vector data, removing a misjudged river ice region, obtaining a river ice region in the region, and completing river ice extraction. According to the method, advantages of optics and SAR images are combined, an attention mechanism and a multi-level feature fusion strategy are constructed, and technical support is provided for refined river ice drawing in the cold and cold mountainous area.

The invention discloses a simplified test natural river ice section flow calculation method, which belongs to the technical field of hydrological test, and comprises the following steps: dividing a section into a plurality of strip units; calculating the effective water depth of each measuring point according to the water depth and the water immersion ice thickness of the measuring point corresponding to each strip unit; calculating the area of each strip unit according to the effective water depth at each measuring point; according to the area of each strip unit, the accumulated section area and the accumulated hydraulic radius from the left bank and the right bank of the section to the strip units are calculated respectively; according to the accumulated section area and the accumulated hydraulic radius from the left bank and the right bank of the section to the strip unit, the relative unit width flow of the sections on the left side and the right side of the strip unit is calculated, and then the comprehensive relative unit width flow of the strip unit is calculated; and calculating the total flow of the section according to the proportional relation between the comprehensive relative unit width flow and the actual unit width flow of the strip unit. According to the method, the full-section flow can be reversely deduced through a small amount of observation, so that the ice period flow testing process is simplified.

The invention relates to the technical field of river ice disaster prevention, and discloses a river freeze-up state prediction method under a multi-flow condition, which comprises the following steps: calculating the flat beach flow at the early stage of river freeze-up; calculating the river sealing volume at the early stage of riverway freezing; obtaining the cooling intensity of the river channel in the cooling process; after correlation analysis is carried out on the accumulated negative air temperature in the time period from the flow to the river closure, the flat beach flow, the river closure flow and the cooling intensity, an accumulated negative air temperature prediction model in the time period from the flow to the river closure is established, a nonlinear least square method is adopted for solving, an optimal fitting coefficient is obtained, and an optimal accumulated negative air temperature prediction model is generated; the accumulated negative air temperature of the current year is obtained, the accumulated negative air temperature is predicted, and the riverway freezing-up state of the current year is obtained through comparison; according to the method, the accumulated negative temperature of the frozen river channel can be accurately obtained by establishing the nonlinear relation between the factors such as the river channel condition (flat beach flow), the sealed river flow and the cooling intensity and the accumulated negative temperature, so that the frozen state of the river reach is accurately judged.

The invention relates to the technical field of river ice condition early warning, and discloses an ice plug prediction method based on fusion of a physical model and machine learning, and the method comprises the steps: obtaining and preprocessing the monitoring data of a to-be-predicted river reach; carrying out parallel calculation on a physical risk index based on a physical mechanism and a machine learning prediction probability based on data driving; performing weighted fusion on the index and the probability to obtain a basic risk index; then, performing multi-stage correction on the basic risk index based on the critical jamming condition and the river channel curvature to obtain a final risk index; and finally, determining and outputting an ice plug risk grade according to a preset threshold value. The mechanism definition of a physical model is combined with the ability of a machine learning model to capture a complex nonlinear relationship. By introducing critical jamming condition correction and river channel geometric feature reinforcement, the reliability of the prediction method under extreme working conditions is ensured, the applicability and prediction precision of the model to different river channel conditions are enhanced, and the comprehensive accuracy of a prediction result is improved.

The invention discloses a river ice range extraction method based on a KAN-UNetFormer model and a Landsat image, and belongs to the technical field of remote sensing geoscience application. The method comprises the following steps: acquiring a multispectral image containing river ice distribution and constructing a training data set; preprocessing the multispectral image, and marking a river ice area of the preprocessed multispectral image; the labeled multispectral image is input into a KAN-UNetFormer model, a comprehensive loss function is constructed, and the model is trained; and obtaining a multispectral image to be extracted, obtaining a binary image by using the trained model, converting the binary image into a vector graph of a river ice range, obtaining a river ice region in the multispectral image, and completing river ice range extraction. The method is good in reliability, and can provide technical support for related research of river ice.

The invention relates to a riverway ice condition identification method based on optics-SAR fusion and adaptive segmentation, and belongs to the technical field of remote sensing image processing and application. Riverway ice condition features are extracted from the optical remote sensing image, and a Ka-SAR feature map is extracted from the Ka-SAR image by adopting an improved high-resolution network; carrying out multi-modal and multi-scale feature fusion on the extracted features, carrying out scale specificity feature extraction by adopting a Gaussian pyramid, and then carrying out weighted fusion on the river ice condition features and the Ka-SAR features on each scale based on a scale specificity weight distribution principle; aggregating the multi-scale fusion features into a final fusion feature map by adopting a bottom-up pyramid reconstruction strategy; improved Kuan filtering is used to optimize the fused feature map, and adaptive threshold segmentation is used to realize ice surface and non-ice surface binary classification in the feature map. The method can achieve the precise segmentation of the ice condition region, and improves the recognition precision of the thin ice region.

The application discloses a kind of river ice distribution intelligent extraction method, device, equipment and storage medium.The method includes obtaining the current river ice image set corresponding to target river ice monitoring area by unmanned aerial vehicle remote sensing;River ice is identified to current river ice image set by pre-set river ice identification network model and obtains corresponding river ice identification image set, U-Net branch network in pre-set river ice identification network model is used to obtain the river ice feature map marked river ice distribution, ResNet branch network is used to obtain the feature distinguishing map distinguishing river bank and river channel, feature distinguishing map and river ice feature map are fused;Finally, according to river ice identification image set, the corresponding river ice distribution data is extracted.The current river ice image set obtained by the pre-set river ice identification network model established by the application can be identified for river ice, and river ice distribution data can be obtained in real time, which not only improves the efficiency of judging ice disaster, but also improves the grasping ability of ice flow process.

The application discloses a kind of river ice surface area and flow velocity calculation method based on shore-based fixed camera, the field model of single monitoring camera fixed on river is constructed, the mapping relationship of image pixel coordinates and actual physical coordinates of river is established, the goal of converting video pixel distance to actual physical distance is realized;Combined with the semantic segmentation result of ice image collected by the camera, the accurate quantitative calculation of the actual area of river ice surface and the ice coverage index is realized, the technical problems that unmanned aerial vehicle, remote sensing image and other technologies cannot continuously and accurately monitor are solved, the equipment cost and deployment difficulty are reduced, and long-term real-time accurate monitoring of river ice conditions is realized.

The invention discloses a river dynamic ice condition extraction method combining spectral information and a temperature time sequence, which comprises the steps of delimiting a river channel range based on a multi-source image by utilizing spectral indexes and topographic features and combining a random forest model and an SNIC segmentation method; in the extracted river mask, the surface temperature is inversed through a thermal infrared band, a statistical single-window model and a harmonic analysis method are utilized, a daily scale LST time sequence is generated in a combined mode, freezing and ablation time periods are determined with 0 DEG C as a threshold value, and the river ice duration time is calculated; identifying the types of ice, snow, water and cloud by adopting an optimized random forest classifier through multispectral features in a river ice period; and by utilizing a temperature constrained ice classification and denoising model, integrating LST constraint and classification results, performing interpolation of cloud pollution pixels, and generating a river ice and accumulated snow coverage product with a spatial resolution of 30 meters. According to the method, river ice monitoring of a continuous time sequence is realized, and the space-time characterization capability of dynamic change of river ice is greatly improved.

The utility model relates to the technical field of river ice treatment, and discloses a river ice monitoring and icebreaking treatment device which comprises a top plate, a lifting plate and a lifting mechanism, the upper surface of the top plate is fixedly connected with a mounting seat, and the mounting seat is fixedly arranged below a bridge floor; the lifting mechanism is arranged on the lower surface of the top plate, connected with the lifting plate and used for controlling the height of the lifting plate, rotating rods are arranged on the two sides of the lifting plate, and connecting chains are fixedly connected to the bottoms of the rotating rods. Through cooperative arrangement of the top plate, the lifting plate and the lifting mechanism, the height of the lifting plate can be adjusted by adjusting the height of the lifting mechanism in use so as to adapt to the height of the river water level in different periods, and the lifting mechanism is further matched with the mounting hole formed in the lifting plate so as to adjust the height of the lifting plate. Corresponding detection equipment such as a flow meter and an ultrasonic thickness gauge can be used.

The invention discloses an alpine region ice flood frost-up period tank water storage increment lag response model construction method. Comprising the following steps: S1, for rivers in an alpine region, collecting ice flood freezing date and river opening date, and day-by-day temperature, flow and tank water storage increment data in the freezing period; s2, constructing a lagging response model of the tank water storage increment in the river ice flood frost-up period in the alpine region; s3, constructing a calculation mode of the tank water storage increment lag response model in the river ice flood frost-up period in the alpine region; s4, establishing a calibration method for parameters of the tank water storage increment lag response model in the river ice flood frost-up period in the alpine region; s5, analyzing the lagging response rule of the tank water storage increment in the river ice flood freezing-up period in the alpine region and applying the model; and S6, evaluating the effect of the tank water storage increment lag response model in the river ice flood frost-up period in the alpine region. According to the method, the influence of water-ice phase state transformation in the ice flood freezing period is considered, the river system lag response model is deepened and developed, and the calculation method is relatively simple.

This invention provides a method and system for inverting river ice thickness based on multiple polarization parameters and texture information. The inversion method includes: acquiring polarization data from a synthetic aperture radar and measured information of a preset area; determining first processed image information and first feature information including polarization parameter information and texture information based on the polarization data; determining pseudo-color image information and establishing a correspondence between the pseudo-color image information and the measured information based on the first processed image information; determining river ice classification information using the pseudo-color image information; determining the average river ice thickness information of the same river ice classification information within the preset area based on the measured information, the first processed image information, and the first feature information; determining an empirical model for river ice thickness based on the average river ice thickness information and the first feature information; and inverting the river ice thickness based on the empirical model and the first feature information. This method enables the inversion of river ice thickness corresponding to different river ice types using multiple parameters, improving the accuracy of the inversion.

The embodiment of the invention discloses a Yellow River ice condition prediction method and device based on multi-model dynamic weighting integrated optimization. A specific embodiment of the method comprises the following steps: for each to-be-predicted year sample, identifying K historical year samples, taking data from which the k year samples are removed as a training set, and taking training data corresponding to the K historical year samples as a verification data set; according to the training set, the four models are retrained, and four models after training updating are obtained; respectively detecting local prediction errors of each model in similar years by using verification data sets corresponding to samples in K historical years according to the updated prediction results of the four models; determining a weighting coefficient of each model on the current training data; and according to each weighting coefficient, carrying out weighted integrated prediction on the Yellow River ice condition prediction result group. According to the embodiment, the model performance can be adaptively adjusted along with the annual scenery features, and the precision and stability of Yellow River scenery prediction are remarkably improved.

The utility model provides a riverway deicing and anti-freezing device. The riverway deicing and anti-freezing device comprises a heating mechanism, a mounting bracket and a moving mechanism, the heating mechanism comprises a power supply and a temperature controller which are electrically connected, the temperature controller is connected with the heating rod through a heating wire, the heating rod is sleeved with a protective cover, and a temperature sensor is arranged in the protective cover; the mounting bracket comprises a group of vertical rods; a steel wire rope is connected between the tops of the two vertical rods; the moving mechanism comprises a moving assembly, a pulley assembly and a winding assembly, the steel wire rope is movably sleeved with the moving assembly, a hanging rope and two moving pull ropes are connected to the moving assembly, the other end of the hanging rope is connected with the protective cover, and the other ends of the moving pull ropes bypass the pulley assembly and are connected with the winding assembly. According to the device, the underwater heating rod is utilized, timed temperature adjustment and heating are performed under the control of the temperature controller, the section river opening condition of the ice period observation station can be remotely controlled in real time, the riverway is prevented from being frozen, and normal, efficient and accurate monitoring of the flow online monitoring system in the river freezing scene is assisted.

The invention relates to the technical field of river ice column collection, and discloses a special device for collecting seasonal frozen river ice columns and performing layered cutting, which comprises a main body capable of walking and positioning on the surface of a river ice layer; the cylinder is arranged at the front end of the body; the icebreaking mechanism is provided with a barrel-shaped drill bit and is used for downwards drilling into a river ice layer and forming an ice column sample and a reserved section; the cut-off mechanism is provided with a heating probe assembly and a liquid nitrogen conveying assembly, the heating probe assembly can be inserted from outside to inside and heat the reserved section, and the liquid nitrogen conveying assembly can output liquid nitrogen spray to the reserved section. A cylindrical drill bit is used for drilling a river ice layer to form an ice column sample and a reserved section, a heating probe assembly is inserted from outside to inside and heats the reserved section, so that the reserved section is locally heated to form thermal expansion stress, then the temperature of the reserved section is instantly reduced through liquid nitrogen spraying, the area is instantly contracted, reverse thermal stress is formed, and the reverse thermal stress is formed. And the ice column is spontaneously broken at the reserved section.

The invention discloses a Yellow River ice condition and water quality coupling simulation method and system, and relates to the field of hydraulic engineering simulation, and the method comprises the following components: S1, physical entity layer construction, S2, data acquisition and transmission, S3, digital twinborn layer construction, and S4, application interaction. The physical entity layer comprising a hydraulic mechanical entity, an ice condition physical field and a water quality physical field is constructed, data are collected in real time in combination with multiple types of sensors, encryption transmission is performed by using a 5G / Beidou dual-mode communication technology, the real-time performance and accuracy of the data are ensured, and a digital twinborn body layer is provided with an ice condition physical field and a water quality physical field. A Kalman filtering algorithm is adopted to carry out fusion processing on data, data noise is effectively eliminated, a standardized model input data set is generated, particularly, dynamic coupling simulation is introduced, and dynamic correlation of hydraulic machinery operation parameters, ice condition parameters and water quality parameters is achieved by establishing a coupling correlation matrix; and the precision and reliability of ice condition and water quality simulation are obviously improved.

This invention discloses a method and apparatus for calculating the inundation range of spring floods considering river ice conditions. The method includes: generating a frozen zone boundary line based on the river centerline and remote sensing image data of the river during the freezing period; and elevation data of topographic points along the river during the freezing period; constructing a two-dimensional hydrodynamic model of the river based on the elevation data of the topographic points and the frozen zone boundary line, and calculating the inundation range. This invention acquires topographic data under freezing conditions and combines it with remote sensing technology to obtain a large-scale, high-frequency understanding of the river's ice-covered area; it uses a two-dimensional hydrodynamic model for calculation to achieve real-time perception of the spatial distribution of the ice cover, reflecting the dynamic compression effect of ice on the river's cross-section; and it distinguishes between ice-covered and non-ice-covered areas through hydrodynamic model parameters, avoiding large deviations in the model's prediction of water level rise and inundation range, which would otherwise fail to provide reliable support for flood control emergency decision-making.