114 results about "Surface water body" patented technology

The invention provides a mine water disaster monitoring and early warning method and system based on multi-source heterogeneous data fusion, and the method comprises the steps: collecting multi-source data of a mining area, carrying out the time-space alignment of the multi-source data, and generating a data set, the multi-source data comprising remote sensing data; preprocessing the data, inputting the preprocessed data into a multi-modal fusion network, and extracting surface water body distribution, lithologic permeability, underground water level and structural fracture characteristics to obtain a three-dimensional hydrogeological static model; the hydrological numerical model based on physical driving is coupled with the static model, and the dynamic model is used for simulating the dynamic change of an underground water flow field and a pollutant diffusion path; based on the dynamic model updated in real time, multi-target collaborative evaluation is carried out to evaluate the mining area water resource, ecological and social collaborative effect; and calling an unmanned aerial vehicle to inspect a leakage position or a settlement position in the hydrogeological risk map based on a multi-target collaborative evaluation result. According to the method, the prediction accuracy is improved through the multi-source data.

The invention discloses a water quality prediction method based on a Transform-LSTM fusion model, and belongs to the technical field of water quality time series data prediction and artificial intelligence. Comprising the following steps: (1) acquiring water quality data from a water quality monitoring station; (2) carrying out pretreatment; (3) screening out water quality characteristic data; (4) dividing into a training set, a verification set and a test set; (5) inputting the data into a Transform-LSTM (Long Short Term Memory) fusion model; (6) embedding water quality data time sequence information by a Transformer encoder through position coding, extracting a global dependency relationship among features by utilizing a multi-head attention mechanism, and optimizing gradient propagation by combining residual connection and layer normalization; (7) the LSTM layer receives the high-order features after Transform coding, and captures a local time sequence dynamic mode; and (8) mapping the extracted water quality time sequence characteristics to a specific prediction result by a regression output layer by adopting a linear activation function, and calculating an evaluation index. According to the method, the water quality change trend of the surface water body can be effectively predicted, and powerful support is provided for water ecological protection and sustainable development.

The invention discloses a multisource remote sensing image surface water body extraction method based on a graph neural network. The SAR image is used as a main part, and the optical image, the digital elevation model and the local incident angle information are fused. Firstly, radiation correction, geometric correction and noise suppression are carried out on SAR data, and multi-source data spatial resolution matching is carried out. And then converting the image into a graph structure by adopting a self-adaptive Bayesian superpixel segmentation method. Then, geometric, texture and physical features are constructed for the superpixel nodes, and feature dimensions are optimized through a feature selection algorithm; and finally, constructing a classification aggregation graph convolutional neural network, wherein the core lies in a self-adaptive microaggregation mechanism of the classification aggregation graph convolutional neural network. According to the mechanism, neighborhood superpixels can be dynamically divided according to categories and feature fusion is carried out, and the recognition capability of the model on water body boundaries and regional heterogeneity is remarkably improved. According to the method, multi-source remote sensing data, superpixel graph structure conversion and an optimized graph convolutional network are comprehensively utilized, and the precision and robustness of water body extraction in the complex surface environment are effectively improved.

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 technical field of environment monitoring, and particularly relates to a quantitative recognition method for contribution of autogenous source organic carbon of a surface water body. Based on the stable isotope ratio and the three-dimensional fluorescence spectrum, the water DOM source analysis method is constructed, the source and characteristics of DOM are comprehensively analyzed, and the characteristic information and contribution of autogenous source organic carbon are specifically recognized. The three-dimensional fluorescence spectrum has the advantages of being rapid in detection, small in sample use amount and the like, DOM sources can be rapidly and qualitatively identified, different DOM sources can be quantitatively calculated through stable isotope ratio analysis, and meanwhile the research area land utilization, hydrological water environment and water quality parameters are combined, so that the DOM sources can be rapidly and qualitatively identified. And the source and migration rule of the DOM in the water body can be determined more comprehensively. The quantitative identification method provided by the invention has the advantages of more comprehensive water DOM research, more complete identification system and more reliable traceability result.

The invention discloses a culture pond monitoring method based on Otsuu-MNDWI collaborative screening and machine learning, and the method is characterized in that the method comprises the following steps: S1, collecting multi-source remote sensing data in a to-be-detected region; s2, carrying out image preprocessing on the surface reflectance data; s3, MNDWI calculation is carried out on the preprocessed surface reflectance data, and a corresponding MNDWI index map is obtained; s4, dividing the MNDWI index map into a water body region and a non-water body region by adopting an Otsu threshold segmentation method; s5, performing water body boundary extraction on the water body area obtained in the step S4 through a Canny algorithm; s6, taking radar VH polarization data, digital elevation data and global surface water body frequency data as auxiliary features, and performing multi-source data fusion and filtering on the auxiliary features and the water body region features obtained in the step S5; and S7, extracting the multi-dimensional feature of each pixel in the water body region processed in the step S6 as an input feature, inputting the input feature into the integrated learning model and training, and outputting a spatial distribution result of the culture pond.

The invention belongs to the technical field of lake and reservoir water source risk prediction, and provides a lake and reservoir water source algae bloom risk early warning system based on a 16S / 18SrRNA gene expression quantity threshold, and the method comprises the following steps: S1, collecting a sample from a lake and reservoir water source surface layer water body; s2, using 7-gate water bloom algae specific primers for blue-green algae, green algae, diatom, euglena, dinoflagellate, chrysophyta and cryptoalga; s3, based on the qPCR standard curve, calculating the copy number of the 16SrRNA / 18SrRNA gene of the seven water bloom algae; s4, when the gene expression quantity of a certain algal bloom algae continuously reaches 106-7 copy number / mL for 7-12 days, determining that the algal bloom algae is in a window phase; according to the threshold value of the gene expression quantity of the water bloom algae 16SrRNA / 18SrRNA, the window period of water bloom algae cells can be accurately recognized, so that early warning of the algae bloom risk in the lake and reservoir water source is achieved, and early warning of algae bloom outbreak in the lake and reservoir water source is achieved one week or above in advance.

The invention discloses a surface water body classification data quality evaluation method based on a remote sensing image, and the method comprises the steps: grouping to-be-classified remote sensing image samples, and distributing different groups to different persons for classification; establishing a square grid; selecting a cross-group grid and a cross-group sample; calculating the percentage of various surface water bodies of each group in the cross-group grid; calculating correlation coefficients of percentages of various surface water bodies among each group in the cross-group grid; and judging whether the groups are abnormal or not according to the correlation coefficient. And based on the similarity principle in the first law of geography, carrying out anomaly detection and quality evaluation on massive classification results by utilizing the classification result correlation coefficients of different classification personnel.

The invention provides a hydrological big data real-time monitoring method and device based on quantum computing and a medium, and belongs to the technical field of hydrological data processing. Hydrological data and change data of a surface water body are collected; determining river course roughness and infiltration coefficient parameters as a hydrological change actual data set by using a quantum annealing process; predicting hydrological change data in the drainage basin based on a random forest regression model; performing comparative analysis on the hydrological change data and a prediction result based on the real-time rainfall data to generate a parameter adjustment instruction; setting a water level change threshold value and a precipitation threshold value; and receiving the precipitation in real time, triggering a historical similar flood event case library retrieval function on the basis of a threshold exceeding condition, and outputting an early warning response record corresponding to a historical event. A quantum walking algorithm is used for simulating flood diffusion, a submerging depth thermodynamic diagram is generated in combination with a digital elevation model, the flood submerging range and depth distribution are rapidly and accurately displayed, and visual and visual support is provided.

The invention belongs to the technical field of water quality monitoring methods, and particularly discloses a stacking integrated machine learning water quality remote sensing inversion method and system based on model contribution degree self-optimization weighting, and the method comprises the following steps: extracting a surface water body range and corresponding water quality monitoring data, integrating the water quality monitoring data into a daily average water quality data set, and calculating the daily average water quality data set; selecting wave bands B2, B3, B4, B5, B6, B7, B8 and B8A, and matching the in-situ water quality monitoring data with the reflectivity of the Sentinel-2 wave band; combining the B2-B8A in pairs to obtain seven mathematical changes, and generating waveband combination features; screening an optimal wave band combination, and carrying out model training to obtain a base model prediction result; and selecting the base model with the optimal determination coefficient R2 as a meta-model, constructing a new feature data set, inputting the new feature data set into the meta-model for final training, and outputting a water quality remote sensing inversion result. By adopting the technical scheme, the high-precision prediction of the water quality parameters is realized by dynamically evaluating the prediction performance of the base model and automatically optimizing the contribution weight of the base model.

The invention discloses an industrial park-oriented pollution accident traceability and risk intelligent prediction system, and relates to the technical field of park pollution prediction, and the system comprises a pollution data collection module which is used for arranging a water quality monitoring terminal in an industrial park factory area, collecting pollution data, and forming structured pollution data; the hydrological structure modeling module is used for constructing a hydrological network diagram structure based on the physical connection relationship between the park underground drainage system and the surface water body and outputting a directed graph; and the pollution path calculation module is used for calculating propagation paths of pollutants on the possible paths and theoretical propagation time corresponding to the paths on the basis of the directed graph structure output by the hydrological structure modeling module. According to the method, a full-path modeling process of pollutants from a discharge source point to a water body diffusion terminal is broken through by constructing a double-drive coupling model, and the model supports dynamic prediction of pollution paths and influence areas under different hydrological situations and process characteristics.

The invention relates to the technical field of underground water state evaluation, and discloses an underground water level dynamic evaluation method based on multi-source data mapping and fluid model correction. The invention aims to solve the technical problems of insufficient underground water level monitoring precision and lack of space details caused by low spatial resolution of existing satellite gravity detection data and difficulty in accurately separating a deep underground water change signal from a land total water reserve signal. According to the method, through space-time reference unification of multi-source heterogeneous data, high-resolution surface texture features are utilized to guide a low-resolution gravitational field to carry out space downscaling reconstruction; surface water body and soil water reserve signals are removed layer by layer in combination with spectral characteristics and a thermal inertia principle; and introducing measured data to construct a spatial error correction curved surface of specific yield parameters, and identifying the underground water funnel by using an image connected domain analysis technology.

The invention relates to the technical field of water resource investigation, in particular to a method and system for calculating dynamic surface water reserves in combination with an SWOT satellite.The method comprises the steps that water surface height data are collected, water surface area calculation is conducted, dynamic weight distribution sensitive to environmental factors and multi-source fusion are conducted, and the water surface area of a target surface water body is obtained; performing water level measurement; fusing and correcting all the water level measurement data obtained by calculation to obtain a corrected water level elevation; acquiring underwater topographic data, and performing feature-level fusion and error minimization optimization on the underwater topographic data by adopting a multi-modal deep learning framework to obtain the underwater topographic data; and calculating the water reserves of the target surface water body. The method solves the problems of single observation data source and susceptibility to environmental interference in the prior art, and has the characteristics of high robustness and all-weather adaptability.

The invention discloses an oil and gas site leakage pollution prediction method based on an HGS, and relates to the field of oil and gas site pollution prediction, and the method comprises the following steps: constructing an integrated three-dimensional geological grid comprising a surface water body, an aeration zone and a water-bearing layer through an HGS platform; on the basis of an integrated three-dimensional geological grid, pollution migration of pollutants in the shaft leakage process is simulated through a three-dimensional underground water flow model, leakage pollution plume changes of the pollutants in underground water are depicted through a solute migration function, and spatial and temporal distribution data of pollution plume migration are output; and obtaining a pollution prediction result based on the spatial and temporal distribution data of pollution plume migration. According to the method, the spatio-temporal evolution law of underground water pollution of the oil and gas field can be accurately displayed, and the problem that in the prior art, only simplified simulation can be conducted on solute transport in an underground water system, oil and gas field leakage pollution scenes under multiple working conditions cannot be accurately simulated, and consequently the oil and gas field leakage pollution prediction accuracy is low is solved.

The invention provides a method for sequencing new organic silicon pollutants in a surface water body according to toxicology priority indexes, and belongs to the technical field of environmental toxicology and ecological risk assessment. The new organic silicon pollutants in the surface water body are sequenced through comprehensive concentration, detection rate, degradation half-life period, toxicity parameters and multi-dimensional indexes such as binding energy and migration ability obtained through molecular docking analysis; according to the method, a molecular docking technology is introduced into an ecological risk evaluation system for the first time, and key risk factors are highlighted by quantifying binding energy of a target substance and a biological receptor and combining differentiated weight distribution. The method has the advantages that 1) the limitation of a single toxicity index is broken through, and multi-factor comprehensive risk quantification is realized; 2) optimizing environment monitoring and governance resource allocation based on the scientific sorting of ToxPi; and 3) scientificity and accuracy of evaluation are improved, and efficient decision support is provided for prevention and control of organosilicon pollution of surface water.

The invention provides a surface water body dynamic monitoring method based on multi-source remote sensing and spatial similarity reconstruction, and relates to the technical field of remote sensing detection. The method comprises the following steps: acquiring a to-be-reconstructed water body distribution diagram sequence collected by an optical remote sensor; searching a reference image with the smallest spatial structure difference with the to-be-reconstructed water body distribution map in the reference image set, and taking the reference image as an optimal reference water body map of the to-be-reconstructed water body distribution map; and carrying out pixel replacement on a missing region in each to-be-reconstructed water body distribution diagram by utilizing a pixel category in the optimal reference water body diagram, and finally obtaining a reconstructed water body distribution diagram sequence. According to the method, pixel-level completion is carried out on a to-be-reconstructed water body distribution diagram acquired by an optical remote sensor by using a pre-constructed missing-free reference image set, so that the integrity of a time sequence water body information image acquired by the optical remote sensor within a period of time is ensured, and the continuity of water body information in time sequence is further ensured; the monitoring requirements of large-range and high-dynamic change water bodies can be met.

The invention discloses an emergency compound agent for coping with short-term total phosphorus increase of a surface water body, and belongs to the field of emergency compound agents for coping with short-term total phosphorus increase of the surface water body. A preparation process comprises the steps of preparing a PAC solution, preparing a diatomite modifier, preparing modified diatomite, preparing the emergency compound agent and the like. The steps of ultrasonic loading, calcining, washing and the like are added in the process, so that the adsorption precipitation capacity of the modified diatomite is improved; and compounding agents with different mass ratios are prepared according to the phosphorus content of the treated water body, so that the application range and the capability are improved. The method is simple to operate, green and environment-friendly, and by modifying the diatomite raw material and increasing the loading degree of the modified diatomite, the adsorption and precipitation capacity of the prepared modified diatomite can be remarkably improved, and the stability after adsorption and precipitation is promoted, so that the use performance and the application range of the prepared emergency compound medicament are effectively improved.

The application discloses a kind of spatiotemporal continuous land surface water body generation methods based on multi-source geospatial data, belong to remote sensing information processing and geographic information technical field.The method includes: obtaining the multi-source geospatial data related to water body distribution, including climate, hydrology and topographic data;It is spatiotemporal resolution and coordinate system, constructs pixel level characteristic variable;Based on existing water body data constructs training sample library;Using random forest or gradient boosting tree and other machine learning methods trains water body distribution reconstruction model;The model is applied to historical or missing time node, and water body distribution prediction result is generated every time phase;Finally form long time sequence, spatially continuous, resolution consistent land surface water body grid data set.The application can effectively fill in remote sensing data missing, improve the spatiotemporal continuity and consistency of water body data, suitable for wide range, long time sequence water body dynamic monitoring and analysis.

The invention relates to the technical field of surface water quality evaluation, in particular to a water quality sampling and evaluating method and device, electronic equipment and a storage medium. Secondly, for each section, constructing a detection data matrix by using a plurality of corresponding detection data vectors according to a time node sequence, and performing dimension transformation on the detection data matrix to obtain section vectors; finding a plurality of similar vectors from the plurality of water quality classes according to each section vector, and constructing the plurality of similar vectors into a reference vector group; and finally, determining the water quality grade of each section according to the reference vector group, and determining the water quality grade of the water body according to the water quality grades of the plurality of sections. According to the method, detection data of a plurality of detection items, a plurality of time nodes and a plurality of sections of the water body are integrated, the water quality of the water body is reflected objectively, few samples are needed, the construction process is simple, and the output result is more accurate and reliable.

The invention provides a nitrogen pollution regulation and control method and device, a storage medium and equipment, and the method comprises the steps: obtaining nitrogen emission data in the production process of industrial and agricultural products, and the total nitrogen of surface water and atmospheric nitrogen oxides in a target region; the method comprises the following steps: acquiring a mapping relation between nitrogen emission of industrial and agricultural products and total nitrogen of surface water and atmospheric nitrogen oxides in a target area, and constructing an economic constraint function and a nitrogen emission constraint function based on an economic development target and an environmental protection target of the target area; and based on second environment data, an economic constraint function, the nitrogen emission constraint function and the mapping relationship, obtaining yield recommendation information of the industrial and agricultural products by using a multi-objective optimization model, and performing production distribution of the industrial and agricultural products according to the yield recommendation information. The production management and control of industrial and agricultural products can be realized by combining economic development and environmental protection, and the local environmental quality is improved while the economic development is guaranteed.

The present invention discloses a tunnel surrounding rock control technology and construction method for supporting a soft rock tunnel before excavation, comprising the following construction steps: S1, designing the spiral radius of an elastic ring support (1) according to the tunnel cross-sectional dimensions, surrounding rock properties, ground stress, elastic-plastic influence zone of the tunnel surrounding rock, and mechanical characteristics of the elastic support, determining the length of the elastic ring support (1) along the preset tunnel strike, whether grouting treatment is required, fixing the anchor length, and arranging the position; S2, performing spiral drilling in a predetermined direction on site using a drilling rig (11) and navigation equipment, and reaching a designated bottom plate; the tunnel surrounding rock control technology and construction method for supporting a soft rock tunnel before excavation of the present invention can be applied not only to soft rock tunnel support, but also to reinforced support of mine tunnels under deep complex geological conditions and high stress environments, as well as reinforced support of deep-sea tunnels and deep underground tunnels, reinforced support of tunnels under surface water bodies, and reinforced support of military underground tunnels.

The invention provides a micro-disturbance under-ice surface water in-situ layered collection monitoring device and method, the device comprises a layered collection device and a monitoring device, the layered collection device comprises a water taking hose, a steering shaft, a support frame, a sliding push rod, an under-ice support frame, an under-ice sampling frame and a fixed support; the steering shaft is installed at the upper end of the supporting frame, the sliding push rod is installed on the outer side wall of the supporting frame, the lower end of the supporting frame is connected with the under-ice sampling frame, the lower end of the under-ice supporting frame is connected with the tail end of the under-ice sampling frame, and the upper end of the under-ice supporting frame is connected with the sliding push rod. The lower end of the water taking hose is inserted into the supporting frame from the upper end of the supporting frame and connected with the water taking hard pipe, and the upper end of the water taking hose is connected to monitoring equipment. The device is simple in structure, convenient to carry and operate and capable of completing high-precision layered fidelity sampling of the water area under ice. And the gas concentration and related environmental parameters of the surface water body under ice can be monitored on site.

The utility model discloses a photovoltaic electricity reinforced horizontal flow constructed wetland reactor which comprises a reactor main body, a water inlet and a water outlet are respectively formed in the top ends of two opposite sides of the reactor main body, a lower gravel layer, a carbon felt layer, an upper gravel layer and a surface water body are sequentially arranged in the reactor main body from bottom to top, and plants are planted on the carbon felt layer; the division module comprises a division plate and a plurality of baffles, the interior of the reactor main body is divided into an anaerobic zone and an aerobic zone by the division plate, two groups of baffles are fixed in the anaerobic zone, and a group of baffles are fixed in the aerobic zone; the electrical stimulation system is mounted on the plant in the aerobic zone, and the bottom of the electrical stimulation system is in contact with the carbon felt layer; the aeration system is mounted at the bottom of the aerobic zone; and the photovoltaic power supply system is connected with the electrical stimulation system and the aeration system. According to the utility model, sewage is deeply treated on the premise of saving energy and utilizing waste, so that the sewage treatment effect is improved.

A kind of mouth of a river backfill drainage pipe network detection device and detection method, detection device includes elbow and shaft;The end of elbow is provided with plugging pipe, the other end is provided with connecting pipe, the shaft is installed on connecting pipe.Detection method includes the following steps: S0: determine suspected well;S1: assemble detection device;S2: detection device is put into water, after plugging pipe is aimed at the mouth of a river, it is inserted and plugged, so that detection device and the pipeline in suspected well form a communicating vessel structure;S3: water is taken from the field surface water body using water taking tool, after adding isotope tracer, mixed water body is poured into detection device from the top of shaft, so that mixed water body enters suspected well;S4: water quality sampling is carried out in suspected well and is detected, when the tracer put in is detected in water sample, then it can be judged that the inspection well is one of the paths of the mouth of a river as surface water invasion;S5: repeat steps S2 to step S4 to detect the water quality of multiple suspected wells.

The utility model discloses an anti-storm surface water iron ion adsorption device, which comprises a floating body and an adsorption body which are fixedly connected together up and down, the floating body drives the adsorption body to float on the surface of a water body, the adsorption body is immersed in the water body and is in contact with the water body, and the adsorption body comprises a shell and an iron ion adsorbent filled in the shell. Water permeable holes are formed in the shell, an adsorbent feeding opening is further formed in the shell, a sealing cover is installed on the adsorbent feeding opening, and connecting ropes are connected to the bottom and the upper portion of the shell. When the iron ion adsorption device is used, water flow enters the adsorption body through the water permeable holes and is in full contact with the iron ion adsorbent, so that iron ions in surface water are adsorbed. Due to the fact that the adsorption body is connected to the fixed position through the connecting rope, the position of the adsorption body is not prone to deviation. Due to the fact that the floating body is located above the adsorption body, water and adsorbent materials are arranged in the adsorption body, and the adsorption body can be kept in a downward state under the action of gravity, the adsorption body is not prone to being knocked over, and good wind wave resistance is achieved.

The application provides a kind of surface water body N2O greenhouse gas emission monitoring method based on remote sensing and intelligent algorithm, first with surface water body as research object, by measured water quality data, explore the key water quality parameters affecting dissolved N2O, using deep neural network algorithm to build dissolved N2O prediction model;Using multi-source remote sensing data, ground hyperspectral information and water quality measured data, build water temperature, pH, dissolved oxygen, inorganic nitrogen remote sensing inversion algorithm;Further combined with dissolved N2O prediction model, water-gas interface N2O emission model, finally build a kind of surface water body N2O greenhouse gas emission monitoring method based on remote sensing and intelligent algorithm, realize the spatial inversion of surface water body N2O generation and emission based on remote sensing.The design fully combines the advantages of remote sensing and intelligent algorithm, more comprehensive, systematic and accurate estimation of surface water body N2O generation and emission, provide scientific monitoring technology and data support for water ecological system greenhouse gas emission reduction.

The application discloses a soil body water seepage early warning device for geotechnical engineering and belongs to the technical field of geotechnical engineering. The soil body water seepage early warning device for geotechnical engineering comprises a landslide, the top surface of a landslide surface layer is provided with a water intercepting ditch, the top surface of the landslide surface layer is provided with a drainage ditch, the inside of the landslide is provided with detection assemblies, the detection assemblies comprise water releasing pipes and alarm mechanisms arranged in the inside of the shallow layer and the weathered mudstone-sandstone interbedding. The landslide surface is drained through the cooperation of the water intercepting ditch, the drainage ditch and the waterfall groove. The water infiltrated due to heavy rainfall or the underground water contained in the slope body can be quickly gathered and discharged through the water releasing pipes, the surface water body can be effectively reduced, the strength and the dead weight of the lower soil body can be maintained, the permeability can be reduced, when the water content in the inside of the slope body reaches a dangerous value, the water level in the inside of the water releasing pipe is increased and drives the alarm mechanism to work to issue an alarm, and meanwhile, the alarm mechanism can accelerate the discharge of the accumulated water in the inside of the water releasing pipe.

The utility model discloses a waterproof device for doors and windows, belongs to the technical field of waterproof of doors and windows, and solves the problems that a window sash of an existing device is easy to cause downward bending of a transverse groove plate, so that the sliding of the window sash is not smooth, the transverse groove plate is horizontally arranged, the flowing speed of water on the top surface of the transverse groove plate through a through hole is slow, and the drainage effect is poor. Comprising a door and window frame, and a groove is formed in the inner wall of the door and window frame; a lower supporting plate with the section in a right triangle shape is fixedly installed on the inner wall of the bottom side of the groove, drainage holes distributed in a linear array mode are formed in the bottom end of the outer vertical face of the groove, and a first guide rail and a second guide rail which are vertically arranged are arranged on the top face of the lower supporting plate. The first guide rail and the second guide rail are supported through the lower supporting plate so that the window sash can smoothly slide on the first guide rail and the second guide rail, rainwater in the groove can be gathered on the top face of the lower supporting plate, then the rainwater flows towards the outer vertical face along the top face of the lower supporting plate, and the rainwater drainage rate can be increased.

The utility model provides a device for extracting a surface water body according to a siphon principle, which comprises a water taking head part, a water collecting head part and a water collecting head part, the hose is connected with the water taking head part; the floating ball is connected to the side part of the water taking head part and the side part of the hose; the hose floats on the water surface by partial buoyancy provided by the floating ball and is fixed by the U-shaped pipe clamp at the top of the dam, the hose outside the dam and the hose floating on the water surface in the dam form a water level difference to generate siphon drainage, electric power or pump drainage is not needed, the total investment cost is lower than that of a traditional pumping system, and the maintenance difficulty is reduced. The unpowered design avoids oil contamination or noise pollution, no mechanical fault is generated, the device is suitable for being matched with ecological sensitive water areas, and the problem of water blooms of water bodies is solved with low cost and high efficiency by ingeniously combining the siphon principle and the floating structure.

The invention discloses a surface water body super-resolution recognition method based on GNSS-R data, relates to the technical field of remote sensing, and aims to solve the problems that an existing surface water body recognition method based on GNSS-R is low in observation efficiency and coverage precision, small-scale water body information cannot be accurately captured, and data redundancy or information loss is easily caused. The invention provides a surface water body super-resolution identification method based on GNSS-R data. The surface water body super-resolution identification method comprises the following steps: preprocessing GNSS-R observation data to obtain effective observation points; modeling each effective observation point as a spatial line segment; constructing a grid system composed of a plurality of grid units, projecting the spatial line segments to the grid system, and calculating weights according to the coverage lengths of the spatial line segments in the grid units; performing weighted statistical calculation on each grid unit to obtain a variable coefficient; and constructing a three-parameter index model, and constructing a water body / non-water body boundary curve in the variable coefficient-average reflectivity characteristic space according to the variable coefficient, thereby realizing accurate extraction of the water body region.