A flood season water level staged floating control system and method

Abstract

The present invention discloses a flood season water level staged floating control system and method thereof. A data acquisition module is used to collect river scouring and silting data, river flow velocity data and dam safety data. A data integration module is used to establish a unified data standard for the collected data, and a database is constructed to store the collected data. 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 visual digital watershed model. In the process of constructing the visual digital watershed model, a data difference detection module is used to detect differences in the data. Through the data association module, an association model between the river scouring and silting data and the dam safety data is established. A risk assessment module is used to construct a dam foundation stability risk assessment model, thereby realizing analysis of the dam foundation stability in the flood season water level staged floating control system.

Description

Technical Field

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

[0002] Monitoring river scouring and dam safety is crucial in water conservancy projects. Traditional methods for monitoring river scouring and silting have numerous limitations. Early adoption of simple surveying tools, such as sounding rods, lacked accuracy and were unable to obtain high-precision underwater topography data, making it difficult to accurately calculate river siltation and scouring. This inability to meet the precise analysis of river channel evolution required by modern water conservancy projects is unsatisfactory. While some technologies utilize a single measuring instrument to obtain data, they lack systematic integration, making it difficult to fully capture river scouring and silting conditions.

[0003] In the past, dam safety monitoring relied on inefficient monitoring point placement and limited data types. Relying on only a few monitoring points to monitor displacement and seepage indicators failed to fully reflect the overall safety status of the dam. Furthermore, there was no unified standardization or management for different types of monitoring data, resulting in incompatible data formats and inconsistent time series. This made data analysis difficult, hindering the timely and accurate assessment of dam safety risks.

[0004] When it comes to data processing and analysis, traditional methods fail to fully explore potential relationships between data. Correlations between river erosion and dam safety data are insufficiently analyzed, failing to quantify their mutual impact, making it difficult to predict potential dam safety issues in advance. Furthermore, existing methods for dam stability risk assessment are either overly simplistic, failing to fully consider complex factors, or complex yet poorly adaptable, preventing flexible adjustments to suit varying engineering geological conditions.

[0005] In summary, 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:

[0008] A data acquisition module for a flood season water level staged rise control system, used to collect river scouring and silting data, river flow velocity data, and dam safety data;

[0009] Data integration module, used to establish unified data standards and database for the data collected by the data acquisition module;

[0010] 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;

[0011] The data analysis module also includes a data difference detection module for the process of building a visual digital watershed model;

[0012] Data association module, used to establish an association model between river scouring and silting data and dam safety data;

[0013] The risk assessment module is used to construct a dam foundation stability risk assessment model.

[0014] Preferably, the following method is specifically used in the difference detection module to perform data difference detection and analysis:

[0015] S11: Use the local window-based filling algorithm to process depressions in DEM data;

[0016] S12: Use the D8 algorithm to calculate the water flow direction of each grid. The slope is calculated 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.

[0017] S13: Determine the water network based on the cumulative flow, set a flow threshold, and when the grid flow cumulative amount exceeds the threshold, determine that the grid is located on the river, thereby extracting the water network;

[0018] S14: In GIS software, use the Intersect or Union overlay analysis tool in ArcGIS to overlay the extracted water network vector data with the collected actual river channel vector data to obtain the intersection or union, and then detect the differences;

[0019] S15: The extraction effect is evaluated by combining the Jaccard coefficient and the accuracy rate;

[0020] S16: Determine weights based on research objectives and data characteristics ;

[0021] S17: Different settings The fusion index is calculated based on the training set and the validation set, and the weight combination with the best performance on the validation set is selected.

[0022] Preferably, in S15, the Jaccard coefficient and accuracy are fused as follows:

[0023] Jaccard coefficient: ;

[0024] Among them, A and B represent the collection of extracted water network and actual river vector data respectively;

[0025] Indicates the number of elements in the set;

[0026] Accuracy formula: ;

[0027] Where A is the extracted water network;

[0028] B is the actual river channel vector data;

[0029] The accuracy formula is integrated with the Jaccard coefficient formula by taking the two indicators into consideration through a weighted average method.

[0030] The following is the fusion formula:

[0031] ;

[0032] 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.

[0033] Preferably, establishing a correlation model between river scouring and silting data and dam safety data specifically includes the following steps:

[0034] S21: Use multivariate statistical analysis methods to establish a data correlation model between river scouring and silting data and dam safety data;

[0035] S22: Assuming that the river scour volume is the independent variable and the dam foundation seepage volume and displacement volume constitute the dependent variable matrix, a regression equation is constructed;

[0036] S23: Calculate the relative impact of river scour on seepage and displacement;

[0037] 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.

[0038] Preferably, in S22, it is assumed that the river scouring amount is the independent variable X, and the dam foundation seepage and displacement amount constitute the dependent variable matrix Y, and the formula is established:

[0039] ;

[0040] Where, is the predicted value of the dependent variable Y;

[0041] is the intercept term;

[0042] is the regression coefficient vector;

[0043] When expressed in terms of seepage and displacement respectively:

[0044] The prediction formula for dam foundation seepage is:

[0045] ;

[0046] Where Q is the predicted value of seepage rate;

[0047] is the seepage rate-related intercept;

[0048] is the regression coefficient of river scour volume on seepage volume;

[0049] S is the amount of river scour;

[0050] Dam foundation displacement prediction formula:

[0051] ;

[0052] Where D is the predicted displacement value;

[0053] is the displacement-related intercept;

[0054] is the regression coefficient of river scour on displacement;

[0055] S is the amount of river scour;

[0056] In S23, the relative influence of river scour on seepage and displacement is calculated using the following formula:

[0057] The relative impact of river scour volume on seepage volume: ;

[0058] The relative impact of river scour on displacement: .

[0059] Preferably, evaluating the model performance in S24 specifically includes using the following indicators to evaluate the model performance;

[0060] The formula for measuring the degree of deviation between the model prediction value and the true value is as follows:

[0061] ;

[0062] in, represents the true value;

[0063] is the predicted value;

[0064] n is the sample size;

[0065] The formula for expressing the model's explanatory power for the dependent variable is:

[0066] ;

[0067] Where, is the mean of the true values.

[0068] 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;

[0069] The limit equilibrium method is used to calculate the forces between the blocks and obtain the preliminary anti-sliding stability safety factor. ;

[0070] Adopt anti-slip stability formula:

[0071] ;

[0072] in, is the friction coefficient of the sliding surface;

[0073] N is the normal force acting on the sliding surface of the strip;

[0074] c is the cohesion of the sliding surface;

[0075] A is the area of the sliding surface of the bar;

[0076] P is the sliding force acting on the bar;

[0077] 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.

[0078] When considering n bars, the force balance equation must be satisfied at the same time and moment balance equations , combined with the distribution function of the force between the blocks, it is deduced that ;

[0079] 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: ;

[0080] According to the actual needs and experience of the project, reasonable determination value;

[0081] Set the threshold of the anti-sliding stability safety factor based on the dam's design standards, project importance, and relevant regulations. ;

[0082] When the calculated comprehensive anti-sliding stability safety factor Less than threshold When an emergency occurs, the system automatically issues an early warning message to notify relevant managers to take corresponding measures;

[0083] 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 i-th block The force arm, n represents the number of bars.

[0084] Preferably, a permeability stability risk assessment is established, and the permeability calculation formula is:

[0085] ;

[0086] Where, J is the penetration force;

[0087] is the weight of water;

[0088] i is the hydraulic gradient;

[0089] The hydraulic gradient i at different locations is calculated using the piezometer data. When the seepage force exceeds the critical anti-seepage strength of the soil, seepage failure occurs.

[0090] Expressed as: ,in is the critical permeability of the soil, determined through indoor geotechnical tests or empirical formulas;

[0091] When river erosion and siltation change 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.

[0092] Preferably, a fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety;

[0093] Determine the evaluation indicator set, including river scouring and siltation related indicators and dam safety indicators;

[0094] Quantify and grade each indicator and determine the corresponding membership function;

[0095] Then, the weight of each indicator is determined by the analytic hierarchy process (AHP);

[0096] The comprehensive risk assessment formula is:

[0097] ;

[0098] Among them, R is the comprehensive risk assessment value;

[0099] is the weight of the i-th indicator;

[0100] is the membership value of the i-th indicator.

[0101] A method for controlling water level rise in stages during flood season, comprising the following steps:

[0102] Step 1: Use the data acquisition module to collect river scouring and silting data, river flow data, and dam safety data;

[0103] 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;

[0104] Step 3: Using geographic information system technology, the spatial location information of the river and dam is associated with the collected data in the data analysis module to construct a visual digital watershed model;

[0105] Step 4: In the process of building a visual digital watershed model, use the data difference detection module to detect differences in the data;

[0106] Step 5: Use the data association module to establish a correlation model between river scouring and silting data and dam safety data;

[0107] Step 6: Use the risk assessment module to construct a dam foundation stability risk assessment model.

[0108] Beneficial technical effects of the present invention:

[0109] 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, utilizes a data integration module to establish a unified data standard for the collected data, and constructs a database to store the collected data. Utilizing geographic information system technology, the spatial location information of the river and the dam is associated with the collected data in a 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. Utilizing a risk assessment module, a dam foundation stability risk assessment model is constructed, thereby realizing 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

[0110] Figure 1 This is a system diagram of a preferred embodiment of a flood season water level staged floating control system according to the present invention;

[0111] 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 thereof. DETAILED DESCRIPTION

[0112] 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 with reference to embodiments and drawings, but the embodiments of the present invention are not limited thereto.

[0113] Collect and integrate data;

[0114] The specific methods are as follows:

[0115] Collecting river scour and sedimentation data, specifically using a multi-beam echo sounder to regularly measure river sections, obtain high-precision underwater topographic data, and accurately calculate the amount of siltation and scour in the river;

[0116] Specifically, the cross-section method is used. Multiple representative vertical sections are selected along the river channel, and the underwater topography data of each section is regularly measured using a multi-beam echo sounder. By comparing the topographic data of the same section at different times, the change in cross-sectional area is calculated, and the amount of siltation or scour of the river channel at that section can be inferred.

[0117] Calculation steps:

[0118] Measuring cross-sectional terrain: At the initial time t1, the terrain data of a certain cross section is measured, and the terrain curve of the cross section is generated through data processing, and the cross-sectional area is calculated .

[0119] At the subsequent time t2, the cross section is measured again to obtain a new cross-sectional area. ;

[0120] Calculate the amount of scouring and silting of the section: , indicating that the section is silted up, and the amount of siltation is Where L is the length of the river represented by the section;

[0121] like , it means that scour occurs, and the scour volume ;

[0122] Calculate the total amount of scouring and silting in the river channel: By accumulating 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.

[0123] Use an Acoustic Doppler Current Profiler (ADCP) to monitor river flow in real time, calculate flow rate based on water level data, and analyze the erosion and sedimentation effects of water flow on the riverbed based on hydrodynamic formulas;

[0124] Specifically, the flow rate measurement method is adopted;

[0125] ADCP transmits 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.

[0126] When taking measurements, install the ADCP on a suitable measurement carrier, such as a survey vessel or a fixed observation platform, to ensure that the instrument can accurately measure the flow velocity at different locations in the river.

[0127] Calculation of water flow cross-sectional area;

[0128] Combined with real-time water level data, the water-flowing cross-sectional area is calculated using the topographic data of the river.

[0129] If the cross-section of the river channel has a regular shape, such as a rectangle or trapezoid, the area can be calculated directly based on the water level and the corresponding cross-section geometric parameters.

[0130] 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 section area A by integration or summation.

[0131] Flow calculation, the flow rate Q is obtained by integrating the velocity profile, usually by multiplying the flow velocity by the corresponding water flow area and summing the results. 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.

[0132] Calculation of hydrodynamic parameters;

[0133] 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.

[0134] 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;

[0135] 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 sedimentation of the riverbed.

[0136] Calculation of Xie Cai coefficient, Xie Cai coefficient C is used to describe the water flow resistance, and the calculation method uses the Manning formula , where n is the roughness coefficient, reflecting the roughness of the riverbed surface;

[0137] R is the hydraulic radius, .

[0138] 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.

[0139] riverbed erosion and sedimentation analysis;

[0140] Sediment transport capacity calculation: using hydrodynamic parameters to calculate the sediment transport capacity of water flow, the calculation formula adopts the May-Peter formula;

[0141] ,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.

[0142] Bed surface shear stress ,in is the density of water, g is the acceleration due to gravity, J is the hydraulic gradient, and R is the hydraulic radius.

[0143] 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 erosive ability and may cause riverbed scour;

[0144] When the actual sediment content is greater than the sediment transport capacity, sediment will accumulate.

[0145] 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.

[0146] At the same time, through the use of UAV 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;

[0147] The specific technical solutions include the following:

[0148] Drone flight planning: plans the drone's flight route based on the length, width and terrain characteristics of the river.

[0149] Ensure that the drone can obtain images covering the entire study area during flight, and that there is sufficient overlap between adjacent images, usually maintained at 60%-80%, to facilitate subsequent image stitching.

[0150] At the same time, set an appropriate 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.

[0151] For large rivers, the flight altitude can be adjusted to 100-200 meters.

[0152] Image acquisition and stitching: Control the drone to perform periodic image acquisition according to the planned route.

[0153] After acquisition, professional image stitching software, such as Pix4D or Agisoft Metashape, is used to stitch together the numerous individual images into a complete river surface image. During the stitching process, the software automatically identifies and matches the image's signature points, achieving precise stitching and generating a digital surface model (DSM) and orthophoto.

[0154] 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.

[0155] The geometric correction algorithm is used to correct the geometric deformation of the image to make it conform to the geographic coordinate system.

[0156] 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.

[0157] Image recognition and feature extraction;

[0158] River boundary extraction: Use edge detection algorithms, such as the Canny algorithm, to process the image and extract the edge information of the river.

[0159] Since the Canny algorithm is sensitive to noise, the image needs to be denoised before application, such as using Gaussian filtering.

[0160] 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, and obtain the accurate river channel boundary.

[0161] The river channel boundaries extracted at different times are superimposed and compared, the displacement and change length of the boundaries are measured, and the change in river channel width is calculated.

[0162] Sandbar feature extraction, based on machine learning or deep learning methods, to train sandbar recognition models.

[0163] 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.

[0164] The trained model can automatically identify the location and extent of sandbars in newly acquired imagery.

[0165] By comparing the changes in the area, shape and position of sandbars in different periods, the increase or decrease in the area of sandbars and the distance they moved are calculated.

[0166] Use shape descriptions such as perimeter, area ratio, and compactness to analyze the shape variations of sandbars.

[0167] Analysis of river channel morphological evolution;

[0168] Quantitative analysis is performed to calculate the rate of change of river channel boundaries and sandbar characteristics, such as the rate of change of river channel width and the rate of change of sandbar area.

[0169] The calculation formula for the river width change rate is: ,in and are the river widths at time t1 and t2 respectively.

[0170] The calculation formula for the sandbar area change rate is: ,in and are the areas of the sandbar at time t1 and t2 respectively.

[0171] Collect dam safety data: Place various sensors inside and at key locations on the dam surface.

[0172] The piezometer monitors the seepage pressure at different elevations of the dam in real time and obtains seepage data;

[0173] The displacement meter uses total station and GPS technology to accurately measure the horizontal and vertical displacement of the dam;

[0174] Stress and strain gauges monitor the stress and strain state of the dam concrete or dam body materials.

[0175] In addition, basic geological data of the dam, including geotechnical parameters and geological structure information, needs to be collected to provide basic support for subsequent analysis.

[0176] Build a data integration platform, specifically by establishing unified data standards and databases to integrate river scouring and silting data with dam safety data;

[0177] Specifically, the International System of Units (SI) will be used for the scour and sedimentation data in river scour and sedimentation data, as well as the seepage and displacement data in dam safety data.

[0178] 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);

[0179] When storing data, a unified number of decimal places should be set according to the data accuracy requirements, such as the scouring volume and sedimentation volume should be accurate to two decimal places;

[0180] Use ISO8601 standard to express time, that is, YYYY-MM-DDTHH:MM:SS±hh:mm format;

[0181] Where YYYY represents the year, MM represents the month, DD represents the day, THH:MM:SS represents the time, and ±hh:mm represents the time zone offset.

[0182] Ensure that the collection time of river scouring and deposition data and dam safety data is in a unified format to facilitate subsequent time series analysis;

[0183] Assign a unique device code to each data collection device, such as a multibeam echo sounder or piezometer;

[0184] The coding rule can be "device type code + area code + device serial number".

[0185] For example, if the device type code of a multibeam echo sounder is MB, the area code is 01, and the serial number of the first device is 001, then the device code is MB01001.

[0186] Through device coding, the source of data collection can be quickly traced.

[0187] The monitoring points on the river section and dam are coded.

[0188] For river sections, the method of "river name code + section number" can be used;

[0189] For dam monitoring points, the method of "dam name code + monitoring point category code + monitoring point serial number" can be used.

[0190] For example, if the serial number of a section of the Yangtze River is 10, its location code is CJ10;

[0191] The piezometer monitoring point number of a certain 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;

[0192] Select an appropriate database management system based on data volume, data type, and application requirements.

[0193] For structured data, such as statistical data on river erosion and siltation and monitoring values of dam safety, relational databases such as MySQL and Oracle can be used.

[0194] For unstructured data, such as river images taken by drones and geological survey reports, non-relational databases such as MongoDB can be used.

[0195] At the same time, considering the real-time nature of data and the need for spatial analysis, spatiotemporal databases such as PostGIS can be introduced to support the storage and query of data with temporal and spatial attributes;

[0196] Conduct database design;

[0197] Data table design:

[0198] River scour and sedimentation data table: contains the collection time, collection equipment code, location code, scour volume, sedimentation volume, river flow rate, and water level fields of river scour and sedimentation data.

[0199] For example, create a table named river_siltation;

[0200] CREATE TABLE river_siltation (

[0201] id INT AUTO_INCREMENT PRIMARY KEY,

[0202] collection_time DATETIME,

[0203] device_code VARCHAR(20),

[0204] location_code VARCHAR(20),

[0205] scouring_amount DECIMAL(10, 2),

[0206] silent_amount DECIMAL(10, 2),

[0207] river_velocity DECIMAL(5, 2),

[0208] water_level DECIMAL(5, 2) );

[0210] Dam safety data table: covers the collection time, collection equipment code, location code, seepage volume, displacement, and stress and strain value fields of dam safety data.

[0211] Create a table named dam_safety;

[0212] CREATE TABLE dam_safety(

[0213] id INT AUTO_INCREMENT PRIMARY KEY,

[0214] collection_time DATETIME,

[0215] device_code VARCHAR(20),

[0216] location_code VARCHAR(20),

[0217] seepage_flow DECIMAL(10,2),

[0218] displacement DECIMAL(5,2),

[0219] stress_strain DECIMAL(5,2) );

[0221] Spatial data table design: Create a spatial data table to store and analyze the spatial information of rivers and dams.

[0222] For example, create a spatial table named river_basin to store the geometric shape and basin range information of the river;

[0223] Create a spatial table named dam_location to store the geographic location and outline information of the dam.

[0224] In PostGIS, use the following statement to create a spatial table:

[0225] CREATE TABLE river_basin (

[0226] id INT AUTO_INCREMENT PRIMARY KEY,

[0227] name VARCHAR(50),

[0228] geom GEOMETRY );

[0230] CREATE TABLE dam_location (

[0231] id INT AUTO_INCREMENT PRIMARY KEY,

[0232] name VARCHAR(50),

[0233] geom GEOMETRY );

[0235] Perform data cleaning and preprocessing;

[0236] Perform outlier detection on the collected river scouring and siltation data and dam safety data;

[0237] For numerical data, use The data were detected based on the principle that data values exceeding the mean ± 3 times the standard deviation were considered as outliers.

[0238] For example, for river flow velocity data, calculate its mean x and standard deviation , if the data value x satisfies or , it is considered an outlier.

[0239] For outliers, they are corrected or deleted according to the actual situation.

[0240] For data with missing values, interpolation is used to fill them.

[0241] For example, for missing values of river water levels, linear interpolation is used to estimate the water level values at adjacent time points.

[0242] Assume that the missing value time point is t0, the adjacent time points are t1 and t2, and the corresponding water level values are y1 and y2, then the missing value y0 is calculated by the formula Calculated.

[0243] Perform data association and integration;

[0244] By collecting time and location codes, river scouring and deposition data can be associated with dam safety data;

[0245] 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:

[0246] SELECT rs.*, ds.*

[0247] FROM river_siltation rs

[0248] JOIN dam_safety ds

[0249] ON rs.collection_time = ds.collection_time

[0250] AND ST_DWithin(rs.geom, ds.geom, 100) -- Assume that 100 meters is the spatial correlation distance;

[0251] The associated data is fused and stored, and a new data table, such as river_dam_integration, can be created to store the integrated data.

[0252] This table contains river erosion and deposition data, dam safety data, and related time and location information for comprehensive analysis;

[0253] CREATE TABLE river_dam_integration (

[0254] id INT AUTO_INCREMENT PRIMARY KEY,

[0255] collection_time DATETIME,

[0256] river_location_code VARCHAR(20),

[0257] dam_location_code VARCHAR(20),

[0258] scouring_amount DECIMAL(10,2),

[0259] silting_amount DECIMAL(10,2),

[0260] seepage_flow DECIMAL(10,2),

[0261] displacement DECIMAL(5,2) );

[0263] Using Geographic Information System (GIS) technology, the spatial location information of river channels and dams is linked with various monitoring data to construct a visual digital watershed model. The specific steps include:

[0264] 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.

[0265] Ensure that the data contains key information such as time and location encoding so that it can be associated with spatial data.

[0266] The monitoring data are matched with the spatial location information of the river and dam through location coding or geographic coordinates.

[0267] 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;

[0268] For dam safety data, the seepage and displacement data can be associated with specific monitoring points on the dam according to the location coding of the dam monitoring points;

[0269] Choose powerful GIS software, ArcGIS and QGIS, as the platform for building digital watershed models;

[0270] 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.

[0271] Use the spatial join tool of GIS software to merge the monitoring data layer with the river channel and dam layers;

[0272] Through spatial join operations, river scouring and deposition data and dam safety data are integrated into the corresponding river and dam layers, so that each spatial feature contains the corresponding monitoring information;

[0273] The construction of the river basin network specifically includes:

[0274] There are some depressions in the DEM data, which will affect the correct calculation of water flow and need to be filled first. A filling algorithm based on a local window is used.

[0275] 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).

[0276] 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 small increment to ensure that water can flow out of the point.

[0277] Calculate water flow direction

[0278] The D8 algorithm is used to calculate the water flow direction of each grid;

[0279] The algorithm considers the elevation difference between each grid and its eight neighboring grids to calculate the slope.

[0280] 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 direction of water flow points to the neighboring grid with the largest slope;

[0281] 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 all upstream grids.

[0282] The specific calculation method is to start from the grid at the edge of the watershed and gradually accumulate it towards the interior of the watershed according to the direction of water flow;

[0283] For each grid, add the cumulative runoff of its upstream neighboring grids and add its own contribution value (set to 1, representing one unit of water flow);

[0284] The water network is determined based on 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.

[0285] Determining the confluence threshold often requires multiple trials based on the actual conditions of the study area. Generally, an initial value can be set based on experience. Then, by comparing it with field survey data or known river network distribution, the threshold can be adjusted continuously until the extracted river network matches the actual situation.

[0286] The extracted water network (represented in raster form) was converted into vector data and then spatially overlaid with the collected river vector data.

[0287] In GIS software, use overlay analysis tools, such as the Intersect or Union tools in ArcGIS, to overlay two vector datasets to obtain their intersection or union;

[0288] 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;

[0289] The present invention adopts the method of integrating the Jaccard coefficient with the accuracy calculation in difference detection to achieve the following specific implementation:

[0290] Jaccard coefficient: , where A and B represent the extracted water network and the actual river vector data set, respectively. Indicates the number of elements in the collection.

[0291] 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.

[0292] Accuracy formula: , where A is the extracted water network and B is the actual river vector data.

[0293] This indicator measures the proportion of the correct part of the extracted water network (i.e. the part that coincides with the actual river channel) in the extracted network, reflecting the accuracy of the extraction results.

[0294] The accuracy formula is integrated with the Jaccard coefficient formula by comprehensively considering the two indicators through the weighted average method.

[0295] The following is the fusion formula:

[0296] ;

[0297] 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.

[0298] The fusion index can be flexibly constructed based on the specific research needs and the emphasis on the accuracy and Jaccard coefficient. The research purpose and data characteristics should be considered. The details are as follows:

[0299] 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. .

[0300] When focusing on the ecological environment of a watershed, such as studying the impact of a water system on an ecosystem, it is necessary to have an overall grasp of the distribution and scope of the water system, and the Jaccard coefficient may be more important.

[0301] Because it can better reflect the similarity between the extracted river network and the actual river system in terms of overall coverage;

[0302] If the actual river vector data is of high quality and accurate, but the extracted water network may contain many misjudgments (that is, some rivers that do not actually exist are extracted), then the weight for improving accuracy can focus on removing the incorrectly extracted parts and optimizing the extraction results.

[0303] On the contrary, if there is a lot of missing or incomplete data, the Jaccard coefficient may better reflect the overall degree of matching, and its weight should be appropriately increased.

[0304] 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 becomes 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 becomes relatively prominent.

[0305] Comparing 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.

[0306] 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.

[0307] Use a validation dataset: Split the dataset into a training set and a validation set, try different weight combinations on the training set to construct the fusion metric, and then verify it on the validation set. Select the one that performs best on the validation set.

[0308] 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.

[0309] By analyzing a large amount of historical data, the correlation coefficients and regression equations between different types of data are determined.

[0310] PLS-R was used to establish a regression model between the river scour volume and the dam foundation seepage and displacement, and the degree of their mutual influence was quantified as follows:

[0311] A model was constructed using partial least squares regression (PLS-R) to quantify the relationship between river scour and dam foundation seepage and displacement.

[0312] Assume that the river scour volume is the independent variable X, and the dam foundation seepage volume and displacement constitute the dependent variable matrix Y.

[0313] , 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.

[0314] When expressed in terms of seepage and displacement respectively:

[0315] Dam foundation seepage prediction formula: ;

[0316] Where Q is the predicted value of seepage flow, is the seepage rate-related intercept, is the regression coefficient of river scour volume to seepage volume, and S is the river scour volume.

[0317] Dam foundation displacement prediction formula: ;

[0318] Where D is the predicted displacement value, is the displacement-related intercept, is the regression coefficient of river scour on displacement, and S is the river scour.

[0319] After the PLS-R model is trained, the regression coefficients are extracted through pls.coef_ to determine the direct effect of river scour on seepage and displacement.

[0320] In order to more intuitively compare the relative impact of river scour on seepage and displacement, the relative impact ratio is calculated.

[0321] The relative impact of river scour volume on seepage volume: ;

[0322] The relative impact of river scour on displacement: ;

[0323] To verify the reliability of the model, the following indicators were used to evaluate the model performance;

[0324] Measures the degree of deviation between the model's predicted value and the true value. ;

[0325] in, represents the true value, is the predicted value, n is the number of samples;

[0326] Indicates the model's ability to explain the dependent variable , where is the mean of the true values.

[0327] After analyzing the correlation between river scouring and silting data and dam safety data, a dam foundation stability risk assessment formula was further established:

[0328] Constructing a fusion evaluation model;

[0329] Block division and calculation: The dam and dam foundation are divided into multiple blocks along the possible sliding surface. The traditional limit equilibrium method is first used to calculate the forces between the blocks and obtain the preliminary anti-sliding stability safety factor. .

[0330] 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 sliding surface, which reflects the friction characteristics between the sliding surface materials. The larger its value, the greater the friction between the materials. N is the normal force acting on the sliding surface of the strip, which is the force perpendicular to the sliding surface. The larger the normal force, the greater the friction generated. c is the cohesion of the sliding surface, which is a kind of bonding force inside the material and represents the mutual attraction between the material particles. The greater the cohesion, the stronger the anti-slip ability of the material. A is the area of the sliding surface of the strip. The size of the sliding surface area will affect the size of the anti-slip force. P is the sliding force acting on the strip, which is the force that causes the strip to slide along the sliding surface. The greater the sliding force, the greater the threat to the anti-slip stability of the dam and the dam foundation.

[0331] Assuming the distribution pattern of the inter-strip forces, the inter-strip forces are corrected based on the Morgenstern-Price method considering the interaction between the strips.

[0332] The modified anti-slip stability safety factor is obtained by solving the equilibrium equation of force and torque through iterative calculation. .

[0333] When considering n bars, the force balance equation must be satisfied at the same time and moment balance equations , combined with the distribution function of the force between the blocks, it is deduced that .

[0334] Set the fusion coefficient 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: .

[0335] According to the actual needs and experience of the project, reasonable determination value.

[0336] For example, when the geological conditions are simple and the interaction between strips and blocks is small, the value, focusing on the calculation results of the traditional limit equilibrium method;

[0337] On the contrary, when the geological conditions are complex and the interaction between strips and blocks is large, it is necessary to reduce value, highlighting the role of the Morgenstern-Price method.

[0338] Set the threshold of the anti-sliding stability safety factor based on the dam's design standards, project importance, and relevant regulations. .

[0339] Real-time monitoring of the dam's operating status, including water level changes and dam displacement information.

[0340] When the calculated comprehensive anti-sliding stability safety factor Less than threshold When a fault occurs, the system automatically issues an early warning message to notify relevant management personnel to take corresponding measures, such as strengthening monitoring and carrying out engineering reinforcement;

[0341] 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 i-th block The force arm, n represents the number of bars.

[0342] The traditional limit equilibrium method is simple to calculate, but it does not fully consider the interaction between bars;

[0343] Although the Morgenstern-Price method takes into account the interaction between bars, the calculation process is complicated.

[0344] 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 in considering the interaction between strips and blocks, thereby improving the accuracy of the evaluation results.

[0345] According to different engineering geological conditions and actual needs, by adjusting the fusion coefficient ,The weights of the two methods are flexibly selected, making the evaluation model more adaptable to various complex situations, and,enhancing the adaptability and practicality of the model.

[0346] Establish a seepage stability risk assessment and evaluate the seepage stability of the dam foundation based on Darcy's law and flow network theory.

[0347] The formula for calculating penetration is: , where J is the penetration force, is the density of water, and i is the hydraulic gradient.

[0348] The hydraulic gradient i at different locations is calculated using the piezometer data. When the seepage force exceeds the critical impermeability strength of the soil, seepage failure may occur.

[0349] It can be expressed as: ,in is the critical seepage force of the soil, determined through indoor geotechnical tests or empirical formulas. When scouring and silting of the river alter the groundwater flow field, the hydraulic gradient i changes. Real-time calculation of J is used to determine whether there is a risk of seepage instability in the dam foundation.

[0350] A fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety.

[0351] First, a set of evaluation indicators was determined, including indicators related to river scour and sedimentation (such as scour depth and sedimentation change rate) and dam safety indicators (seepage change rate and displacement rate). Each indicator was quantitatively graded and the corresponding membership function was determined.

[0352] 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 i-th indicator, is the membership value of the i-th indicator.

[0353] 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.

[0354] The above is only a further embodiment of the present invention, but the scope of protection 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 falls within the scope of protection of the present invention.

Claims

1. A flood season water level staged floating control system and data acquisition module for collecting 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 acquisition 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; Its characteristics are: The data analysis module also includes a data difference detection module for the process of building a visual digital watershed model; Data association module, used to establish an association model between river scouring and silting data and dam safety data; Risk assessment module, used to build a dam foundation stability risk assessment model; In the difference detection module, the following methods are used to perform data difference detection and analysis: S11: Use the 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. The slope is calculated 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 based on the cumulative flow, set a flow threshold, and when the grid flow cumulative amount exceeds the threshold, determine that the grid is located on the river, thereby extracting the water network; S14: In GIS software, use the Intersect or Union overlay analysis tool in ArcGIS to overlay the extracted water network vector data with the collected actual river channel vector data to obtain the intersection or union, and then detect the differences; S15: The extraction effect is evaluated by combining the Jaccard coefficient and the accuracy rate; S16: Determine weights based on research objectives and data characteristics ; S17: Different settings The fusion index is calculated based on the training set and the validation set, and the weight combination with the best performance on the validation set is selected.

2. A flood season water level staged floating control system according to claim 1, 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 the set; Accuracy formula: ; Where A is the extracted water network; B is the actual river channel vector data; The accuracy formula is integrated 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.

3. 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 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 and the dam foundation seepage volume and displacement volume constitute the dependent variable matrix, a 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.

4. A flood season water level staged floating control system according to claim 3, characterized in that: In S22, it is assumed that the river scour volume is the independent variable X, and the dam foundation seepage volume and displacement constitute the dependent variable matrix Y. The formula is established: ； Where, is the predicted value of the dependent variable Y; β0 is the intercept term; β1 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 rate; 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 displacement value; 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 scour on seepage and displacement is calculated using the following formula: The relative impact of river scour volume on seepage volume: ; The relative impact of river scour on displacement: .

5. A flood season water level staged floating control system according to claim 4, 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: ； Among them, y i represents the true value; is the predicted value; n is the sample size; The formula for expressing the model's explanatory power for the dependent variable is: ； Where, is the mean of the true values.

6. 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 blocks and obtain the preliminary anti-sliding stability safety factor. ; Adopt anti-slip stability 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 bar; 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 at the same time and moment balance equations , combined with the distribution function of the force between the blocks, 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, reasonable determination value; Set the threshold of the anti-sliding stability safety factor based on the dam's design standards, project importance, and relevant regulations. ; When the calculated comprehensive anti-sliding stability safety factor Less than threshold When an emergency occurs, the system automatically issues an early warning message to notify relevant managers to take corresponding measures; in, represents the force between the bars, X i Refers to the tangential force acting on the bar, x i represents the arm of the tangential force Xi on the i-th bar, is the inter-block force on the i-th block The force arm, n represents the number of bars.

7. A flood season water level staged floating control system according to claim 6, characterized in that: A penetration stability risk assessment model was established, and the penetration force 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 using the piezometer data. When the seepage force exceeds the critical anti-seepage strength of the soil, seepage failure occurs. Expressed as: ,in is the critical permeability of the soil, determined through indoor geotechnical tests or empirical formulas; When river erosion and siltation change 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.

8. A flood season water level staged floating control system according to claim 7, characterized in that: A fuzzy comprehensive evaluation method is used to construct a comprehensive risk assessment model for dam safety; Determine the evaluation indicator 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; w i is the weight of the i-th indicator; μ i is the membership value of the i-th indicator.

9. A method for controlling the staged rise of water levels during flood season, based on the staged rise of water levels during flood season control system according to any one of claims 1 to 8, characterized in that: The steps include: Step 1: Use the data acquisition module to collect river scouring and silting data, river flow 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: Using geographic information system technology, the spatial location information of the river and dam is associated with the collected data in the data analysis module to construct 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: Use the data association module to establish a correlation model between river scouring and silting data and dam safety data; Step 6: Use the risk assessment module to construct a dam foundation stability risk assessment model.

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