Flood season water level staging floating control system and method thereof

Abstract

The invention discloses a flood season water level staged floating control system and method, and the method employs a data collection module to collect river channel erosion and deposition data, river channel flow velocity data and dam safety data, employs a data integration module to establish a unified data standard for the collected data, builds a database, stores the collected data in the database, and carries out the control of the flood season water level staged floating. A geographic information system technology is applied, spatial position information of a river channel and a dam is associated with collected data in a data analysis module, a visual digital watershed model is constructed, in the process of constructing the visual digital watershed model, a data difference detection module is used for carrying out difference detection on the data, and a data association module is used for carrying out data analysis on the data. A correlation model of river channel erosion and deposition data and dam safety data is established, a risk assessment module is utilized to construct a dam foundation stability risk assessment model, and analysis about dam foundation stability in a flood season water level staging floating control system is achieved.

Description

Technical Field

[0001] The invention relates to a water level staged floating control system, in particular to a flood season water level staged floating control system and a method thereof, and belongs to the technical field of water level staged floating control systems. Background Art

[0002] In the field of water conservancy projects, river scouring and dam safety monitoring is extremely important. Traditional river scouring and silting monitoring methods have many limitations. The simple measurement tools used in the early days, such as sounding rods, have low measurement accuracy and cannot obtain high-precision underwater topographic data. It is difficult to accurately calculate the amount of siltation and scouring of the river, and cannot meet the needs of modern water conservancy projects for accurate analysis of river evolution. Although some technologies use a single measuring instrument to obtain data, they lack systematic integration and it is difficult to fully grasp the scouring and silting of the river.

[0003] In the past, the layout of monitoring points for dam safety monitoring was not scientific enough, and the types of monitoring data were limited. Relying on only a few monitoring points to monitor displacement and seepage indicators cannot fully reflect the overall safety status of the dam. Moreover, there is no unified standard and management for different types of monitoring data, and there are problems such as incompatible data formats and inconsistent time series, which makes data analysis difficult and makes it impossible to timely and accurately assess dam safety risks.

[0004] In terms of data processing and analysis, traditional methods cannot fully explore the potential relationship between data. The correlation analysis between river scouring and siltation data and dam safety data is insufficient, and the mutual influence between the two cannot be quantified, making it difficult to predict possible safety problems of dams in advance. At the same time, in the dam stability risk assessment, the existing assessment methods are either too simple in calculation and do not fully consider complex factors, or are complex in calculation but poor in adaptability, and cannot flexibly adjust the assessment model according to different engineering geological conditions.

[0005] In summary, the existing technologies have obvious deficiencies in the comprehensiveness of river scouring and siltation and dam safety monitoring, the systematicness of data processing, and the accuracy and adaptability of risk assessment. A new technical solution is urgently needed to solve these problems. Summary of the invention

[0006] The main purpose of the present invention is to provide a flood season water level staged floating control system and method.

[0007] The purpose of the present invention can be achieved by adopting the following technical solutions: A data acquisition module for a flood season water level staged floating control system, used to collect river scouring and silting data, river flow velocity data and dam safety data; Data integration module, used to establish unified data standards and database for the data collected by the data collection module; The data analysis module uses geographic information system technology to associate the spatial location information of the river and dam with the data collected by the data acquisition module to build a visual digital watershed model; The data analysis module also includes a data difference detection module used in the process of building a visualized digital watershed model; Data association module, used to establish the association model between river scouring and silting data and dam safety data; The risk assessment module is used to construct a dam foundation stability risk assessment model.

[0008] Preferably, the following method is specifically used in the difference detection module to perform data difference detection and analysis: S11: Use a local window-based filling algorithm to process depressions in DEM data; S12: Use the D8 algorithm to calculate the water flow direction of each grid, and calculate the slope based on the elevation difference between the grid and its eight neighboring grids. The water flow direction points to the neighboring grid with the largest slope. S13: Determine the water network according to the cumulative amount of confluence, set the confluence threshold, and when the cumulative amount of grid confluence exceeds the threshold, determine that the grid is located on the river channel, thereby extracting the water network; S14: In GIS software, use the Intersect or Union overlay analysis tool of ArcGIS to overlay the extracted water network vector data with the collected actual river vector data to obtain the intersection or union to detect the difference; S15: The extraction effect is evaluated by combining the Jaccard coefficient with the accuracy rate; S16: Determine weights based on research objectives and data characteristics ; S17: Different settings The fusion index is calculated by using the training set and the validation set for comparative analysis, and the weight combination with the best performance on the validation set is selected.

[0009] Preferably, in S15, the Jaccard coefficient and accuracy are fused as follows: Jaccard coefficient: ; Among them, A and B represent the collection of extracted water network and actual river vector data respectively; Indicates the number of elements in a set; Accuracy formula: ; Among them, A is the extracted water network; B is the actual river vector data; Fuse the accuracy formula and the Jaccard coefficient formula, and the fusion method is to comprehensively consider the two indicators through the weighted average method; The following is the fusion formula: ; Among them, is a weight coefficient, and its value range is between 0 and 1, which is used to adjust the relative importance of the accuracy rate and the Jaccard coefficient in the comprehensive index.

[0010] Preferably, the establishment of the correlation model between the river channel erosion and deposition data and the dam safety data specifically includes the following steps: S21: Use the multivariate statistical analysis method to establish a data correlation model between the river channel erosion and deposition data and the dam safety data; S22: Assume that the river channel erosion amount is the independent variable, and the dam foundation seepage flow rate and displacement amount form the dependent variable matrix, and construct a regression equation; S23: Calculate the relative influence proportion of the river channel erosion amount on the seepage flow rate and displacement amount; S24: Evaluate the model performance, measure the deviation degree between the model prediction value and the true value, and the explanatory ability of the model to the dependent variable, and verify the reliability of the model.

[0011] Preferably, in S22, assume that the river channel erosion amount is the independent variable X, and the dam foundation seepage flow rate and displacement amount form the dependent variable matrix Y, and establish the formula: ; In the formula, is the predicted value of the dependent variable Y; is the intercept term; is the regression coefficient vector; When expressed by the seepage flow rate and displacement amount respectively: The predicted formula for the dam foundation seepage flow rate is: ; Among them, Q is the predicted value of the seepage flow rate; is the intercept related to the seepage flow rate; is the regression coefficient of the river channel erosion amount on the seepage flow rate; S is the river channel erosion amount; The predicted formula for the dam foundation displacement amount: ; Among them, D is the predicted value of the displacement amount; is the intercept related to the displacement amount; is the regression coefficient of river scour on displacement; S is the amount of river scour; In S23, the relative influence of river scouring on seepage and displacement is calculated using the following formula: The relative impact of river scouring on seepage volume: ; The relative impact of river scouring on displacement: .

[0012] Preferably, evaluating the model performance in S24 specifically includes evaluating the model performance using the following indicators; The formula for measuring the degree of deviation between the model prediction value and the true value is as follows: ; in, represents the true value; is the predicted value; n is the sample size; The formula for the model's ability to explain the dependent variable is: ; In the formula, is the mean of the true values.

[0013] Preferably, in constructing the dam foundation stability risk assessment model, the sliding surface of the dam and the dam foundation is divided into a plurality of strips; The limit equilibrium method is used to calculate the forces between the strips and blocks, and the preliminary anti-sliding stability safety factor is obtained. ; Adopt anti-slip stable formula: ; in, is the friction coefficient of the sliding surface; N is the normal force acting on the sliding surface of the strip; c is the cohesion of the sliding surface; A is the area of ​​the bar sliding surface; P is the sliding force acting on the bar; Assuming the distribution pattern of inter-strip forces, the inter-strip forces are corrected based on the Morgenstern-Price method considering the interaction between the strips. When considering n bars, the force balance equation must be satisfied simultaneously and the moment balance equation , combined with the distribution function of the force between the strips, it is deduced that ; Set the fusion coefficient ,and The safety factors obtained by the two methods are combined by weighted average to obtain the comprehensive anti-sliding stability safety factor , the calculation formula is: ; According to the actual needs and experience of the project, reasonably determine value; Set the threshold of the anti-sliding stability safety factor according to the design standard of the dam, the importance of the project and relevant specifications ; When the calculated comprehensive anti-sliding stability safety factor Less than threshold When a warning message is sent, the system will automatically issue a warning message to notify relevant managers to take corresponding measures; in, Represents the force between the bars, Refers to the tangential force acting on the bar, Represents the tangential force on the i-th bar The force arm, is the inter-block force on the ith block The moment arm is n, and n represents the number of bars.

[0014] Preferably, a permeability stability risk assessment is established, and the permeability calculation formula is: ; Where, J is the penetration force; is the weight of water; i is the hydraulic gradient; The hydraulic gradient i at different locations is calculated through the piezometer data. When the permeability exceeds the critical anti-seepage strength of the soil, permeability failure occurs. It is expressed as: ,in is the critical permeability of soil, determined by indoor geotechnical tests or empirical formulas; When river scouring and silting changes the groundwater flow field, the hydraulic gradient i changes, and J is calculated in real time to determine whether there is a seepage stability risk in the dam foundation.

[0015] Preferably, a fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety; Determine the evaluation index set, including river scouring and siltation related indicators and dam safety indicators; Quantify and grade each indicator and determine the corresponding membership function; Then, the weight of each indicator is determined by analytic hierarchy process (AHP); The comprehensive risk assessment formula is: ; Among them, R is the comprehensive risk assessment value; is the weight of the i-th indicator; is the membership value of the i-th indicator.

[0016] A method for controlling water level floating in stages during flood season, comprising the following steps: Step 1: Use the data acquisition module to collect river scouring and silting data, river flow velocity data and dam safety data; Step 2: Use the data integration module to establish a unified data standard for the collected data and build a database to store the collected data; Step 3: Use geographic information system technology to associate the spatial location information of the river and dam with the collected data in the data analysis module to build a visual digital watershed model; Step 4: In the process of building a visual digital watershed model, use the data difference detection module to detect data differences; Step 5: Establish a correlation model between river scouring and silting data and dam safety data through the data correlation module; Step 6: Use the risk assessment module to construct a dam foundation stability risk assessment model.

[0017] Beneficial technical effects of the present invention: The present invention provides a flood season water level staged floating control system and method thereof. The present invention utilizes a data acquisition module to collect river scouring and silting data, river flow velocity data and dam safety data, adopts a data integration module to establish a unified data standard for the collected data, and constructs a database to store the collected data. The geographic information system technology is used to associate the spatial position information of the river and the dam with the collected data in the data analysis module to construct a visualized digital watershed model. In the process of constructing the visualized digital watershed model, a data difference detection module is used to perform difference detection on the data. Through the data association module, an association model between the river scouring and silting data and the dam safety data is established. The risk assessment module is used to construct a dam foundation stability risk assessment model, thereby realizing the analysis of the dam foundation stability in the flood season water level staged floating control system, and providing important reference value for the regulation of the staged floating control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A system diagram of a preferred embodiment of a flood season water level staged floating control system according to the present invention; Figure 2 The present invention is a flow chart of a preferred embodiment of a flood season water level staged floating control system and method according to the present invention. DETAILED DESCRIPTION

[0019] In order to make the technical solution of the present invention more clear and specific to those skilled in the art, the present invention is further described in detail below in conjunction with embodiments and drawings, but the implementation manner of the present invention is not limited thereto.

[0020] Collect and integrate data; The specific method is as follows: Collect river scouring and silting data, including using multi-beam echo sounders to regularly measure river sections, obtain high-precision underwater topographic data, and accurately calculate the silting and scouring volume of the river; Specifically, the cross-section method is used to select multiple representative vertical sections on the river channel and use a multi-beam echo sounder to regularly measure the underwater topographic data of each section. By comparing the topographic data of the same section at different times, the change in the cross-sectional area is calculated, and then the siltation or scouring amount of the river channel at the section is inferred; Calculation steps: Measuring cross-sectional topography: At the initial time t 1 , measure the terrain data of a certain section, generate the terrain curve of the section through data processing, and calculate the cross-sectional area .

[0021] At the subsequent time t 2 , measure the section again and get the new cross-sectional area ; Calculate the cross-section scouring and silting volume: , indicating that the section is silted up, and the amount of siltation Where L is the length of the river represented by the section; like , it means that scouring has occurred, and the scouring amount ; Calculate the total amount of scouring and silting in the river channel: By adding up the scouring and silting amounts of multiple sections in the river channel, the total amount of silting or scouring in the entire river channel can be obtained. , n is the number of sections.

[0022] Use the Acoustic Doppler Current Profiler (ADCP) to monitor the river flow velocity in real time, calculate the flow rate based on the water level data, and analyze the erosion and siltation of the riverbed based on the hydrodynamic formula; Specifically, the flow velocity measurement method is adopted; ADCP emits sound waves into the water body and measures the flow velocity of water layers at different depths based on the Doppler frequency shift effect of the sound waves, thereby obtaining the flow velocity profile data of the water body.

[0023] When taking measurements, install the ADCP on a suitable measurement carrier, such as a measurement ship or a fixed observation platform, to ensure that the instrument can accurately measure the flow velocity at different locations in the river; Calculation of water flow cross-sectional area; Combined with real-time water level data, the topographic data of the river channel is used to calculate the cross-sectional area of ​​water flow.

[0024] If the cross-section of the river is of regular shape, such as a rectangle or trapezoid, the area can be calculated directly based on the water level and the corresponding cross-sectional geometric parameters.

[0025] For irregularly shaped sections, it is necessary to use a geographic information system (GIS) or a digital river topographic map to divide the section into multiple small units and calculate the water-passing cross-sectional area A by integration or summation.

[0026] Flow calculation: The flow rate Q is obtained by integrating the velocity profile. It is usually calculated by multiplying the velocity by the corresponding water flow area and summing them. The formula is: ,in is the flow velocity of the i-th layer, is the water flow area corresponding to the i-th layer, and n is the number of layers.

[0027] Calculation of hydrodynamic parameters; Average flow velocity calculation: calculate the average flow velocity V of the entire water flow section. The formula is: The average flow velocity reflects the overall flow velocity of water in the entire section and is an important parameter for subsequent analysis.

[0028] Reynolds number calculation, Reynolds number Re is used to determine the flow state of water flow, and its calculation formula is: , where D is the hydraulic diameter, for non-circular sections, , P is the wet perimeter; v is the kinematic viscosity of the fluid. When the Reynolds number is greater than a certain critical value, the water flow is turbulent, otherwise it is laminar. The flow state has a significant impact on the erosion and siltation of the riverbed.

[0029] Calculation of Xie Cai coefficient. Xie Cai coefficient C is used to describe water flow resistance. The calculation method uses Manning formula , where n is the roughness coefficient, reflecting the roughness of the riverbed surface; R is the hydraulic radius, .

[0030] The Scheherazade coefficient determines the energy loss between the water flow and the riverbed, which in turn affects the effect of the water flow on the riverbed.

[0031] Riverbed erosion and siltation analysis; Sediment transport capacity calculation: the sediment transport capacity of water flow is calculated using hydrodynamic parameters, and the calculation formula is the Mayer-Peter formula; ,in is the sediment transport rate per width, K is the coefficient, is the bed shear stress, Initiate shear stress for sediment, is the weight of sediment particles, The weight of water.

[0032] Bed surface shear stress ,in is the density of water, g is the acceleration due to gravity, J is the hydraulic slope, and R is the hydraulic radius.

[0033] Erosion and sedimentation judgment, compare the actual sediment content with the sediment transport capacity of the water flow: when the actual sediment content is less than the sediment transport capacity, the water flow has erosion capacity and may cause riverbed scour; When the actual sediment content is greater than the sediment transport capacity, silt will accumulate.

[0034] The erosion and siltation status of the riverbed can be determined by real-time measurement or estimation of the actual sediment content and comparison with the calculated sediment transport capacity.

[0035] At the same time, through the use of drone low-altitude photogrammetry technology, river surface images are periodically acquired, and image recognition algorithms are used to extract changes in river boundaries and sandbar features; The specific technical solutions include the following: Drone flight planning plans the flight route of the drone based on the length, width and terrain characteristics of the river.

[0036] Ensure that the drone can obtain images covering the entire study area during the flight, and that there is sufficient overlap between adjacent images, usually maintained at 60%-80%, to facilitate subsequent image stitching.

[0037] At the same time, set a suitable flight altitude to ensure that the image resolution meets the requirements for extracting river channel features. For example, for small rivers, the flight altitude can be set at 50-100 meters to obtain images with a resolution of 5-10 cm / pixel. For large rivers, the flight altitude can be adjusted to 100-200 meters. Image acquisition and stitching, according to the planned route, control the drone to perform periodic image acquisition.

[0038] After the acquisition is completed, professional image stitching software, such as Pix4D and Agisoft Metashape, is used to stitch a large number of single images into a complete river surface image. During the stitching process, the software automatically identifies the feature points of the same name in the image, and achieves accurate image stitching by matching these feature points, and generates a digital surface model (DSM) and orthophoto map. Image correction and enhancement: In order to eliminate image distortion and brightness differences caused by the UAV's flight posture and lighting conditions, the stitched images need to be corrected and enhanced.

[0039] The geometric correction algorithm is used to correct the geometric deformation of the image to make it conform to the geographic coordinate system.

[0040] At the same time, histogram equalization and contrast stretching methods are used to enhance the contrast of the image, highlight the river boundaries and sandbar features, and provide a clear data source for subsequent image recognition. Image recognition and feature extraction; River boundary extraction: Use edge detection algorithms, such as the Canny algorithm, to process the image and extract the edge information of the river.

[0041] Since the Canny algorithm is sensitive to noise, the image needs to be denoised before application, such as using Gaussian filtering.

[0042] In addition, in order to improve the extraction accuracy, the threshold segmentation algorithm is combined to separate the river channel from the background according to the grayscale difference between the river channel and the surrounding objects in the image, so as to obtain the precise river channel boundary.

[0043] The river boundaries extracted at different times are superimposed and compared, the displacement and change length of the boundaries are measured, and the change in river width is calculated. Sandbar feature extraction, based on machine learning or deep learning methods, training sandbar recognition models.

[0044] A large number of labeled images containing sandbars are used as training samples, and a convolutional neural network (CNN), such as the U-Net model, is used to train the images so that they can accurately identify sandbars.

[0045] The trained model can automatically identify the location and extent of sand bars in newly acquired imagery.

[0046] By comparing the changes in the area, shape and position of the sandbar at different times, the increase or decrease in the area of ​​the sandbar and the distance it has moved are calculated.

[0047] Use shape descriptions such as perimeter, area ratio, and compactness to analyze the shape variation of sandbars. Analysis of river channel morphology evolution; Quantitative analysis is performed to calculate the change rates of river channel boundaries and sandbar characteristics, such as the change rate of river channel width and the change rate of sandbar area.

[0048] The calculation formula of river width change rate is: ,in and t 1 and t 2 The width of the river at that moment.

[0049] The calculation formula for the change rate of sandbar area is: ,in and t 1 and t 2 The area of ​​the sandbar at the moment. Collect dam safety data: Arrange various sensors inside and at key locations on the surface of the dam.

[0050] The piezometer monitors the seepage pressure at different elevations of the dam in real time and obtains seepage data; The displacement meter uses total station and GPS technology to accurately measure the horizontal and vertical displacement of the dam; Stress strain gauges monitor the stress and strain state of dam concrete or dam body materials.

[0051] In addition, it is necessary to collect basic geological data of the dam, including geotechnical mechanics parameters and geological structure information, to provide basic support for subsequent analysis.

[0052] Build a data integration platform, specifically establish a unified data standard and database, and integrate river scouring and silting data with dam safety data; Specifically, the International System of Units (SI) is used for the scouring and silting data in river scouring and silting data, and the seepage and displacement data in dam safety data. For example, the unit of length is meter (m), the unit of flow is cubic meter per second (m³ / s), and the unit of pressure is Pascal (Pa); When storing data, set a uniform number of decimal places according to the data accuracy requirements, such as the scouring volume and sedimentation volume to two decimal places; The time is expressed using the ISO8601 standard, i.e. the format of YYYY-MM-DDTHH:MM:SS±hh:mm; Among them, YYYY represents the year, MM represents the month, DD represents the date, THH:MM:SS represents the time, and ±hh:mm represents the time zone offset; Ensure that the collection time of river scouring and siltation data and dam safety data has a unified format to facilitate subsequent time series analysis; Assign a unique device code to each data collection device, such as multibeam echo sounder and piezometer; The coding rule can be in the form of "device type code + area code + device serial number".

[0053] For example, if the equipment type code of a multibeam echo sounder is MB, the area code is 01, and the serial number of the first equipment is 001, then the equipment code is MB01001.

[0054] Through device coding, the source of data collection can be quickly traced. Encode the locations of monitoring points on river sections and dams.

[0055] For river sections, the method of “river name code + section number” can be used; For dam monitoring points, the method of “dam name code + monitoring point category code + monitoring point serial number” can be used.

[0056] For example, if the serial number of a section of the Yangtze River is 10, its location code is CJ10; The piezometer monitoring point number of a dam is 5, and its location code is DB0105, where DB represents the dam name code and 01 represents the piezometer monitoring point category code; Select an appropriate database management system based on data volume, data type, and application requirements.

[0057] For structured data, such as statistical data on river scouring and siltation and monitoring values ​​of dam safety, relational databases such as MySQL and Oracle can be used.

[0058] For unstructured data, such as river images taken by drones and geological survey reports, non-relational databases such as MongoDB can be used.

[0059] At the same time, considering the real-time nature of data and the spatial analysis requirements, spatiotemporal databases such as PostGIS can be introduced to support the storage and query of data with temporal and spatial attributes; Conduct database design; Data table design: River scouring and silting data table: contains the collection time, collection equipment code, location code, scouring volume, silting volume, river flow rate, and water level fields of river scouring and silting data.

[0060] For example, create a table named river_siltation; CREATE TABLE river_siltation ( id INT AUTO_INCREMENT PRIMARY KEY, collection_time DATETIME, device_code VARCHAR(20), location_code VARCHAR(20), scouring_amount DECIMAL(10, 2), silent_amount DECIMAL(10, 2), river_velocity DECIMAL(5, 2), water_level DECIMAL(5, 2) ); Dam safety data table: covers the collection time, collection equipment code, location code, seepage volume, displacement, and stress-strain value fields of dam safety data.

[0061] Create a table named dam_safety; CREATE TABLE dam_safety( id INT AUTO_INCREMENT PRIMARY KEY, collection_time DATETIME, device_code VARCHAR(20), location_code VARCHAR(20), seepage_flow DECIMAL(10,2), displacement DECIMAL(5,2), stress_strain DECIMAL(5,2) ); Spatial data table design: Create a spatial data table to store and analyze the spatial information of rivers and dams.

[0062] For example, create a spatial table named river_basin to store the geometric shape and basin range information of the river; Create a spatial table named dam_location to store the geographic location and outline information of the dam.

[0063] In PostGIS, use the following statement to create a spatial table: CREATE TABLE river_basin ( id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(50), geom GEOMETRY ); CREATE TABLE dam_location ( id INT AUTO_INCREMENT PRIMARY KEY, name VARCHAR(50), geom GEOMETRY ); Perform data cleaning and preprocessing; Perform outlier detection on the collected river scouring and silting data and dam safety data; For numerical data, use The detection was carried out according to the principle that data values ​​exceeding the mean ± 3 times the standard deviation were considered abnormal values.

[0064] For example, for river flow data, calculate its mean x and standard deviation , if the data value x satisfies or , it is considered as an outlier.

[0065] For outliers, they are corrected or deleted according to the actual situation.

[0066] For data with missing values, interpolation is used to fill them.

[0067] For example, for missing values ​​of river water levels, linear interpolation is used to estimate them based on water level values ​​at adjacent time points.

[0068] Let the missing value time point be t 0 , the adjacent time point is t 1 and t 2 , the corresponding water level value is y 1 and 2 , then the missing value y 0 By formula Calculated.

[0069] Perform data correlation and integration; By collecting time and location codes, the river scouring and silting data are associated with the dam safety data; When performing data analysis, use SQL statements to query river scouring and silting data and dam safety data at the same time and similar locations: SELECT rs.*, ds.* FROM river_siltation rs JOIN dam_safety ds ON rs.collection_time = ds.collection_time AND ST_DWithin(rs.geom, ds.geom, 100) -- Assume that 100 meters is the spatial correlation distance; The associated data can be fused and stored, and a new data table, such as river_dam_integration, can be created to store the integrated data.

[0070] The table contains river erosion and deposition data, dam safety data and related time and location information for comprehensive analysis; CREATE TABLE river_dam_integration ( id INT AUTO_INCREMENT PRIMARY KEY, collection_time DATETIME, river_location_code VARCHAR(20), dam_location_code VARCHAR(20), scouring_amount DECIMAL(10,2), silting_amount DECIMAL(10,2), seepage_flow DECIMAL(10,2), displacement DECIMAL(5,2) ); Using geographic information system (GIS) technology, the spatial location information of the river and dam is associated with various monitoring data to build a visual digital watershed model, including the following: Convert previously collected river scouring and siltation data and dam safety monitoring data into a format recognizable by GIS software, such as CSV or Excel tables.

[0071] Ensure that the data contains key information such as time and location encoding so that it can be associated with spatial data. The monitoring data are matched with the spatial location information of the river and dam through location coding or geographic coordinates.

[0072] For example, for river scouring and sedimentation data, the corresponding scouring and sedimentation data can be associated with the corresponding positions of the river according to the location coding of the river section; For dam safety data, the seepage and displacement data can be associated with specific monitoring points of the dam according to the location coding of the dam monitoring points; Choose powerful GIS software, ArcGIS and QGIS, as the platform for building digital watershed models; Import the processed spatial data and monitoring data into the GIS software and create corresponding layers, such as river layer, dam layer, and monitoring data layer. Use the spatial connection tool of GIS software to merge the monitoring data layer with the river channel and dam layer; Through spatial join operations, river scouring and silting data and dam safety data are integrated into the corresponding river and dam layers, so that each spatial element contains the corresponding monitoring information; The construction of river basin network includes: There are some depressions in the DEM data, which will affect the correct calculation of water flow and need to be filled first, using a filling algorithm based on a local window.

[0073] Iterate over each grid point in the DEM data, and for each point, check the grid value within its surrounding neighborhood (such as a 3×3 or 5×5 window).

[0074] If the elevation value of the current point is lower than some points in its neighborhood, the elevation value of the current point is updated to the minimum value in the neighborhood plus a tiny increment to ensure that the water can flow out of the point.

[0075] Calculate water flow direction The D8 algorithm is used to calculate the water flow direction of each grid; The algorithm considers the elevation difference between each grid and its eight neighboring grids and calculates the slope.

[0076] The slope calculation formula is: , where (i, j) is the coordinate of the current grid, (m, n) is the coordinate of the neighboring grid, S is the slope, and the water flow direction points to the neighboring grid with the largest slope; By tracking the direction of water flow, the cumulative flow of each grid is calculated, that is, the total amount of water flowing into the grid from the upstream of the grid.

[0077] The specific calculation method is to start from the grid at the edge of the watershed and gradually accumulate it towards the inside of the watershed according to the direction of water flow; For each grid, add the accumulated runoff of its upstream neighboring grids and add its own contribution value (set to 1, representing one unit of water flow); The water network is determined according to the cumulative flow, and an appropriate flow threshold is set. When the cumulative flow of a grid exceeds the threshold, the grid is considered to be located on the river channel, thereby extracting the water network.

[0078] The determination of the confluence threshold usually requires multiple experiments based on the actual situation of the study area. Generally speaking, an initial value can be set based on experience, and then the threshold can be adjusted continuously by comparing it with field survey data or known water system distribution until the extracted water system network is consistent with the actual situation.

[0079] The extracted water network (represented in raster form) was converted into vector data and then spatially overlaid with the collected river vector data.

[0080] In GIS software, use overlay analysis tools, such as Intersect or Union tools in ArcGIS, to overlay two vector datasets to obtain their intersection or union; By comparing the superimposed data sets, the differences between the extracted water network and the actual river vector data are detected, and the coincidence index between the two is calculated; The present invention adopts the method of integrating the Jaccard coefficient with the accuracy calculation in the difference detection to achieve the specific implementation as follows: Jaccard coefficient: , where A and B represent the collection of extracted water network and actual river vector data, respectively. Indicates the number of elements in the collection.

[0081] The value of the Jaccard coefficient is between 0 and 1. The closer the value is to 1, the higher the overlap between the two.

[0082] Accuracy formula: , where A is the extracted water network and B is the actual river vector data.

[0083] This indicator measures the proportion of the correct part of the extracted water network (i.e. the part that overlaps with the actual river channel) in the extracted network, reflecting the accuracy of the extraction results.

[0084] The accuracy formula is integrated with the Jaccard coefficient formula by taking the two indicators into comprehensive consideration through the weighted average method.

[0085] The following is the fusion formula: ; in, It is a weight coefficient ranging from 0 to 1, which is used to adjust the relative importance of accuracy and Jaccard coefficient in the comprehensive index.

[0086] According to the specific research needs and the importance of the two indicators of accuracy and Jaccard coefficient, the fusion index can be flexibly constructed. The research purpose and data characteristics need to be considered. The details are as follows: If the purpose of the study is to accurately calculate the storage and flow of water resources in the basin, you may pay more attention to accuracy, because an accurate water network is very important for accurately estimating water balance and water flow paths. In this case, you can appropriately increase the weight of accuracy. .

[0087] When focusing on the ecological environment of a watershed, such as studying the impact of a water system on the ecosystem, it is necessary to have an overall grasp of the distribution and range of the water system, so the Jaccard coefficient may be more important.

[0088] Because it can better reflect the similarity between the extracted water network and the actual water system in terms of overall coverage; If the actual river vector data is of high quality and accurate, but the extracted water network may have many misjudgments (that is, some rivers that do not actually exist are extracted), then the weight for improving the accuracy can focus on removing the erroneously extracted parts and optimizing the extraction results.

[0089] On the contrary, if there are more missing or incomplete data, the Jaccard coefficient may better reflect the overall degree of matching, and its weight should be appropriately increased.

[0090] Data distribution: Observe the distribution of water systems in the data. If the water systems are sparsely distributed, a small amount of erroneous extraction will have a greater impact on the overall situation, and accuracy will become more critical. If the water systems are densely distributed, the overall overlap can better reflect the extraction effect, and the importance of the Jaccard coefficient will be relatively prominent.

[0091] Comparison of different weight combinations: By setting different Values, such as =0.2, 0.4, 0.6, 0.8, calculate the fusion index, and compare and analyze it with the actual situation.

[0092] For example, the fusion indicators can be applied to the water network assessment in different river basins to observe which weight combination's assessment results are more consistent with the actual water resources status and ecological environment characteristics.

[0093] Use a validation dataset: Divide the dataset into a training set and a validation set, try different weight combinations on the training set to construct the fusion index, and then validate it on the validation set. Select the one that performs best on the validation set.

[0094] A data association model was established, and multivariate statistical analysis methods, such as principal component analysis and partial least squares regression, were used to find the potential relationship between river scouring and siltation data and dam safety data.

[0095] By analyzing a large amount of historical data, the correlation coefficients and regression equations between different types of data are determined.

[0096] PLS-R was used to establish a regression model between the river scouring volume and the dam foundation seepage and displacement, and the degree of mutual influence between them was quantified as follows: A model was constructed by partial least squares regression (PLS-R) to quantify the relationship between river scour and dam foundation seepage and displacement.

[0097] Assume that the river scouring volume is the independent variable X, and the dam foundation seepage and displacement constitute the dependent variable matrix Y.

[0098] , where is the predicted value of the dependent variable Y, is the intercept term, is the regression coefficient vector, which can be obtained through pls.coef_ in Python modeling.

[0099] When expressed in terms of seepage and displacement respectively: Dam foundation seepage prediction formula: ; Where Q is the predicted value of seepage flow, is the seepage rate-related intercept, is the regression coefficient of river scouring volume to seepage volume, and S is the river scouring volume.

[0100] Dam foundation displacement prediction formula: ; Where D is the predicted displacement value, is the displacement-related intercept, is the regression coefficient of river scour to displacement, and S is the river scour.

[0101] After the PLS-R model was trained, the regression coefficients were extracted through pls.coef_ to determine the direct effect of river scour on seepage and displacement.

[0102] In order to more intuitively compare the relative size of the impact of river scour on seepage and displacement, the relative impact ratio was calculated.

[0103] The relative impact of river scouring on seepage volume: ; The relative impact of river scouring on displacement: ; To verify the reliability of the model, the following indicators were used to evaluate the model performance; Measures the degree of deviation between the model prediction value and the true value. ; in, represents the true value, is the predicted value, n is the sample size; Indicates the model's ability to explain the dependent variable , where is the mean of the true values.

[0104] After analyzing the correlation between river scouring and silting data and dam safety data, a dam foundation stability risk assessment formula was further established: Constructing a fusion evaluation model; Chunking and calculation: Divide the dam and its foundation into multiple slices along the possible slip surface. First, use the traditional limit equilibrium method to calculate the forces between slices and obtain the preliminary anti-sliding stability safety factor. .

[0105] The calculation formula follows the anti-sliding stability formula of the traditional limit equilibrium method: , where each parameter represents: is the friction coefficient of the slip surface, reflecting the friction characteristics between the materials of the slip surface. The larger its value, the greater the friction force between the materials. N is the normal force acting on the slip surface of the slice, which is the force perpendicular to the slip surface. The greater the normal force, generally the greater the friction force generated. c is the cohesion of the slip surface, which is a kind of cohesive force inside the material, representing the mutual attraction between the material particles. The greater the cohesion, the stronger the anti-sliding ability of the material. A is the area of the slip surface of the slice, and the size of the slip surface area will affect the magnitude of the anti-sliding force. P is the sliding force acting on the slice, which is the force that causes the slice to slide along the slip surface. The greater the sliding force, the greater the threat to the anti-sliding stability of the dam and its foundation.

[0106] Assume the distribution pattern of the forces between slices, consider the interaction between slices based on the Morgenstern-Price method, and correct the forces between slices.

[0107] Solve the equilibrium equations of forces and moments through iterative calculation to obtain the corrected anti-sliding stability safety factor .

[0108] When considering n slices, it is necessary to simultaneously satisfy the force equilibrium equation and the moment equilibrium equation . Combining with the distribution function of the forces between slices, after derivation, we get .

[0109] Set the fusion coefficient , and fuse the safety factors obtained by the two methods through weighted average to obtain the comprehensive anti-sliding stability safety factor , and the calculation formula is: .

[0110] According to the actual engineering requirements and experience, reasonably determine the value.

[0111] For example, when the geological conditions are simple and the interaction between slices is small, the value can be appropriately increased, emphasizing the calculation results of the traditional limit equilibrium method; On the contrary, when the geological conditions are complex and the interaction between slices is large, reduce the value to highlight the role of the Morgenstern-Price method.

[0112] Set the threshold of the anti-sliding stability safety factor according to the design standard of the dam, the importance of the project and relevant specifications .

[0113] Real-time monitoring of the dam's operating status, including water level changes and dam displacement information.

[0114] When the calculated comprehensive anti-sliding stability safety factor Less than threshold When a warning message is sent, the system will automatically issue an early warning message to notify relevant management personnel to take corresponding measures, such as strengthening monitoring and carrying out engineering reinforcement; in, Represents the force between the bars, Refers to the tangential force acting on the bar, Represents the tangential force on the i-th bar The force arm, is the inter-block force on the ith block The moment arm is n, and n represents the number of bars.

[0115] The traditional limit equilibrium method is simple to calculate, but it does not fully consider the interaction between bars; Although the Morgenstern-Price method takes into account the interaction between bars, the calculation process is complicated.

[0116] By integrating the two methods, we can not only take advantage of the simplicity of calculation of the traditional limit equilibrium method, but also utilize the characteristics of the Morgenstern-Price method to consider the interaction between strips and blocks, thereby improving the accuracy of the evaluation results.

[0117] According to different engineering geological conditions and actual needs, by adjusting the fusion coefficient , the weights of the two methods are flexibly selected to make the evaluation model more adaptable to various complex situations and enhance the adaptability and practicality of the model.

[0118] A seepage stability risk assessment was established to evaluate the seepage stability of the dam foundation based on Darcy’s law and flow network theory.

[0119] The formula for calculating penetration is: , where J is the penetration force, is the density of water and i is the hydraulic gradient.

[0120] The hydraulic gradient i at different locations is calculated using the piezometer data. When the permeability exceeds the critical impermeability strength of the soil, permeability failure may occur.

[0121] It can be expressed as: ,in is the critical permeability of the soil, which is determined by indoor geotechnical tests or empirical formulas. When the scouring and silting of the river changes the groundwater flow field, the hydraulic gradient i changes, and J is calculated in real time to determine whether there is a risk of seepage stability in the dam foundation.

[0122] A fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety.

[0123] First, determine the evaluation index set, including river scouring and sedimentation related indicators (such as scouring depth, sedimentation change rate) and dam safety indicators (seepage change rate, displacement rate). Quantify and grade each indicator and determine the corresponding membership function.

[0124] Then, the weight of each indicator is determined by the analytic hierarchy process (AHP). The comprehensive risk assessment formula is: , where R is the comprehensive risk assessment value, is the weight of the ith indicator, is the membership value of the i-th indicator.

[0125] The risk levels are divided according to the size of the R value, such as low risk, medium risk, and high risk, providing a scientific basis for dam safety management.

[0126] The above description is only a further embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and concept of the present invention within the scope disclosed by the present invention, which belongs to the protection scope of the present invention.

Claims

1. A flood season water level staged floating control system, data acquisition module, used to collect river scouring and silting data, river flow data and dam safety data; Data integration module, used to establish unified data standards and database for the data collected by the data collection module; The data analysis module uses geographic information system technology to associate the spatial location information of the river and dam with the data collected by the data acquisition module to build a visual digital watershed model; Features: The data analysis module also includes a data difference detection module used in the process of building a visualized digital watershed model; Data association module, used to establish the association model between river scouring and silting data and dam safety data; The risk assessment module is used to construct a dam foundation stability risk assessment model.

2. A flood season water level staged floating control system according to claim 1, characterized in that: In the difference detection module, the following methods are specifically used to perform data difference detection and analysis: S11: Use a local window-based filling algorithm to process depressions in DEM data; S12: Use the D8 algorithm to calculate the water flow direction of each grid, and calculate the slope based on the elevation difference between the grid and its eight neighboring grids. The water flow direction points to the neighboring grid with the largest slope. S13: Determine the water network according to the cumulative amount of confluence, set the confluence threshold, and when the cumulative amount of grid confluence exceeds the threshold, determine that the grid is located on the river channel, thereby extracting the water network; S14: In GIS software, use the Intersect or Union overlay analysis tool of ArcGIS to overlay the extracted water network vector data with the collected actual river vector data to obtain the intersection or union to detect the difference; S15: The extraction effect is evaluated by combining the Jaccard coefficient with the accuracy rate; S16: Determine weights based on research objectives and data characteristics ; S17: Different settings The fusion index is calculated by using the training set and the validation set for comparative analysis, and the weight combination with the best performance on the validation set is selected.

3. A flood season water level staged floating control system according to claim 2, characterized in that: In S15, the Jaccard coefficient and accuracy are fused as follows: Jaccard coefficient ; Among them, A and B represent the collection of extracted water network and actual river vector data respectively; Indicates the number of elements in a set; Accuracy formula: ; Among them, A is the extracted water network; B is the actual river vector data; The accuracy formula is combined with the Jaccard coefficient formula by taking the two indicators into consideration through a weighted average method. The following is the fusion formula: ; in, It is a weight coefficient ranging from 0 to 1, which is used to adjust the relative importance of accuracy and Jaccard coefficient in the comprehensive index.

4. A flood season water level staged floating control system according to claim 1, characterized in that: The establishment of the correlation model between river scouring and silting data and dam safety data specifically includes the following steps: S21: Use multivariate statistical analysis methods to establish a data correlation model between river scouring and silting data and dam safety data; S22: Assuming that the river scour volume is the independent variable, the dam foundation seepage volume and displacement volume constitute the dependent variable matrix, the regression equation is constructed; S23: Calculate the relative impact of river scour on seepage and displacement; S24: Evaluate model performance to measure the degree of deviation between the model's predicted value and the true value and the model's ability to explain the dependent variable, and verify the reliability of the model.

5. A flood season water level staged floating control system according to claim 4, characterized in that: In S22, it is assumed that the river scouring volume is the independent variable X, and the dam foundation seepage and displacement constitute the dependent variable matrix Y, and the formula is established: ； In the formula, is the predicted value of the dependent variable Y; is the intercept term; is the regression coefficient vector; When expressed in terms of seepage and displacement respectively: The prediction formula for dam foundation seepage is: ； Where Q is the predicted value of seepage volume; is the seepage rate-related intercept; is the regression coefficient of river scour volume on seepage volume; S is the amount of river scour; Dam foundation displacement prediction formula: ； Where D is the predicted value of displacement; is the displacement-related intercept; is the regression coefficient of river scour on displacement; S is the amount of river scour; In S23, the relative influence of river scouring on seepage and displacement is calculated using the following formula: The relative impact of river scouring on seepage volume: ; The relative impact of river scouring on displacement: .

6. A flood season water level staged floating control system according to claim 5, characterized in that: In S24, evaluating the model performance specifically includes using the following indicators to evaluate the model performance; The formula for measuring the degree of deviation between the model prediction value and the true value is as follows: ； in, represents the true value; is the predicted value; n is the sample size; The formula for the model's ability to explain the dependent variable is: ； In the formula, is the mean of the true values.

7. A flood season water level staged floating control system according to claim 1, characterized in that: The construction of the dam foundation stability risk assessment model specifically includes dividing the sliding surface of the dam and the dam foundation into multiple strips; The limit equilibrium method is used to calculate the forces between the strips and blocks, and the preliminary anti-sliding stability safety factor is obtained. ; Adopt anti-slip stable formula: ; in, is the friction coefficient of the sliding surface; N is the normal force acting on the sliding surface of the strip; c is the cohesion of the sliding surface; A is the area of ​​the sliding surface of the strip; P is the sliding force acting on the bar; Assuming the distribution pattern of inter-strip forces, the inter-strip forces are corrected based on the Morgenstern-Price method considering the interaction between the strips. When considering n bars, the force balance equation must be satisfied simultaneously and the moment balance equation , combined with the distribution function of the force between the strips, it is deduced that ; Set the fusion coefficient ,and The safety factors obtained by the two methods are combined by weighted average to obtain the comprehensive anti-sliding stability safety factor , the calculation formula is: ; According to the actual needs and experience of the project, reasonably determine value; Set the threshold of the anti-sliding stability safety factor according to the design standard of the dam, the importance of the project and relevant specifications ; When the calculated comprehensive anti-sliding stability safety factor Less than threshold When a warning message is sent, the system will automatically issue a warning message to notify relevant managers to take corresponding measures; in, Represents the force between the bars, Refers to the tangential force acting on the bar, Represents the tangential force on the i-th bar The force arm, is the inter-block force on the ith block The moment arm is n, and n represents the number of bars.

8. A flood season water level staged floating control system according to claim 7, characterized in that: A permeability stability risk assessment model was established, and the permeability calculation formula was: ； Where, J is the penetration force; is the weight of water; i is the hydraulic gradient; The hydraulic gradient i at different locations is calculated through the piezometer data. When the permeability exceeds the critical anti-seepage strength of the soil, permeability failure occurs. It is expressed as: ,in is the critical permeability of soil, determined by indoor geotechnical tests or empirical formulas; When river scouring and silting changes the groundwater flow field, the hydraulic gradient i changes, and J is calculated in real time to determine whether there is a seepage stability risk in the dam foundation.

9. A flood season water level staged floating control system according to claim 8, characterized in that: The fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety; Determine the evaluation index set, including river scouring and siltation related indicators and dam safety indicators; Quantify and grade each indicator and determine the corresponding membership function; Then, the weight of each indicator is determined through the analytic hierarchy process; The comprehensive risk assessment formula is: ； Among them, R is the comprehensive risk assessment value; is the weight of the i-th indicator; is the membership value of the i-th indicator.

10. A flood season water level staged floating control method, based on a flood season water level staged floating control system according to any one of claims 1 to 9, characterized in that: The steps include: Step 1: Use the data acquisition module to collect river scouring and silting data, river flow velocity data and dam safety data; Step 2: Use the data integration module to establish a unified data standard for the collected data and build a database to store the collected data; Step 3: Use geographic information system technology to associate the spatial location information of the river and dam with the collected data in the data analysis module to build a visual digital watershed model; Step 4: In the process of building a visual digital watershed model, use the data difference detection module to detect data differences; Step 5: Establish a correlation model between river scouring and silting data and dam safety data through the data correlation module; Step 6: Use the risk assessment module to construct a dam foundation stability risk assessment model.

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