Water level calculation method based on triangulation network area weighting

Abstract

The invention relates to the technical field of water level identification, in particular to a water level calculation method based on triangulation network area weighting. The method comprises the following steps: arranging a plurality of water level observation stations, and recording spatial position coordinates of the water level observation stations; obtaining a time sequence water level observation value of each water level observation station in the observation period; extracting a corresponding instantaneous water level from the time sequence water level observation value according to the sampling time; establishing a triangulation relation according to the spatial positions of the underwater measuring points and the water level observation stations, calculating the area ratio between the underwater measuring points and the adjacent water level observation stations, and automatically reconstructing the triangulation relation and updating the area ratio when the number and the positions of the water level observation stations are changed; according to the invention, accurate identification of the water level of the underwater measuring point is realized through water level calculation, so that the identification accuracy and the calculation efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of water level calculation technology, and in particular to a water level calculation method based on triangular network area weighting. Background Technology

[0002] Currently, underwater topographic surveying primarily employs single-beam echo sounding, mainly using GNSS positioning and echo sounders to measure water depth. Due to operational needs, it is sometimes necessary to convert the depth measurements of underwater measuring points into specific required elevation values ​​(i.e., water level correction). Given the uncertainty of water levels in inland waterways, the industry generally lacks a mature and fixed model and formula, leading to varying water level correction methods and slight differences in the corrected values. Under relatively fixed observation environments and conditions, the main cause of these differences lies in the different water level estimation methods. Currently, the industry commonly uses a single "comprehensive water level value" for correction. However, when estimating the water level at a specific measuring point, factors such as location and time are all relevant. Therefore, different water level values ​​should be applied to each measuring point based on its location, time, the location of the water level station, and the time of the water level reading. Based on the analysis of the causes of these errors and through analysis and verification of measured data, a mathematical model is proposed to solve the problem of underwater measuring point water level calculation, thereby achieving accurate reproduction of the water level at each measuring point at any given time. Summary of the Invention

[0003] Therefore, it is necessary to provide a water level calculation method based on triangular network area weighting to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a water level calculation method based on triangular network area weighting includes the following steps: Step S1: Deploy multiple water level observation stations and record the spatial coordinates of each station; obtain the time series water level observation values ​​of each station within the observation period. Step S2: Collect the instantaneous coordinates and sampling time of the underwater measuring point, and extract the corresponding instantaneous water level from the time series water level observations based on the sampling time; Step S3: Establish a triangulation relationship based on the spatial location of underwater measuring points and water level observation stations, calculate the area ratio between underwater measuring points and adjacent water level observation stations, and automatically reconstruct the triangulation relationship and update the area ratio when the number and location of water level observation stations change. Step S4: Calculate and process the extracted instantaneous water level combined with the area ratio to obtain the water level value of the underwater measuring point at the sampling time, thereby identifying the water level.

[0005] The beneficial effects of this invention are: (1) By setting up multiple water level observation stations and recording their spatial coordinates, a water level observation network covering the monitoring area can be formed, which not only ensures the integrity and continuity of the collected data, but also provides a stable basis for subsequent spatial interpolation and calculation.

[0006] (2) The introduction of a triangulation method based on spatial location relationship and the calculation of the area ratio between underwater measuring points and adjacent water level observation stations can effectively reflect the spatial belonging relationship of underwater measuring points in the observation area, making the water level calculation results more geometrically consistent. When the number or location of observation stations is adjusted, the mechanism of automatically reconstructing the triangulation relationship further ensures the adaptability of the method in dynamic environments and the continuity of calculation results.

[0007] (3) By using the ratio of instantaneous water level to area for weighted calculation, a comprehensive water level value matching the location of the underwater measuring point can be obtained, thereby avoiding the problem of insufficient representativeness of data from a single observation station and making the water level calculation results more accurate and robust. Compared with traditional methods, this method can reduce errors caused by local abnormal water levels and improve the ability to reflect the actual water level status of underwater measuring points. Attached Figure Description

[0008] Figure 1 This is a flowchart illustrating the steps of a water level calculation method based on triangular network area weighting. Figure 2 A schematic diagram showing the layout of water level stations and the locations of measuring points; Figure 3 This is a schematic diagram of time series water level interpolation; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0009] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0010] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] To achieve the above objectives, please refer to Figures 1 to 3 A water level calculation method based on triangular network area weighting includes the following steps: Step S1: Deploy multiple water level observation stations and record the spatial coordinates of each station; obtain the time series water level observation values ​​of each station within the observation period. Step S2: Collect the instantaneous coordinates and sampling time of the underwater measuring point, and extract the corresponding instantaneous water level from the time series water level observations based on the sampling time; Step S3: Establish a triangulation relationship based on the spatial location of underwater measuring points and water level observation stations, calculate the area ratio between underwater measuring points and adjacent water level observation stations, and automatically reconstruct the triangulation relationship and update the area ratio when the number and location of water level observation stations change. Step S4: Calculate and process the extracted instantaneous water level combined with the area ratio to obtain the water level value of the underwater measuring point at the sampling time, thereby identifying the water level.

[0013] In one embodiment, multiple water level observation stations are deployed along the studied river section. Each station is equipped with a pressure-type water level gauge, and its spatial coordinates are obtained using GNSS-RTK positioning. These coordinates are then uniformly converted to numerical values ​​in a Cartesian coordinate system. Each station continuously collects water level values ​​according to a set observation period (e.g., 1 minute), and the collection results are stored in the form of timestamps, forming time-series water level observation data. When collecting underwater measurement point data, an Acoustic Doppler Current Profiler (ADCP) is used to locate the measurement point, obtain its instantaneous spatial coordinates, and record the sampling time. Based on the sampling time, the observation value closest to that time is extracted from the aforementioned time-series water level observation data. If necessary, interpolation can be performed based on the water level values ​​of previous and subsequent times to obtain the instantaneous water level corresponding to the sampling time.

[0014] Subsequently, the spatial locations of the underwater measuring points and the water level observation stations are input into the computer program. A triangular mesh relationship is established using the Delaunay triangulation method, and the area ratio between the measuring point and adjacent observation stations is calculated. When the number or location of observation stations changes, the program automatically triggers a triangulation and reconstruction operation, updating the area ratio of the measuring points in real time. Finally, the extracted instantaneous water level and the corresponding area ratio are input into the calculation module. A weighted calculation is then performed to obtain the water level value of the underwater measuring point at the sampling time, thus enabling the identification of the water level at that measuring point.

[0015] In another embodiment, when setting up water level observation stations along the river section, a combination of water gauges and video monitoring is used to obtain water level observation values. Specifically, no fewer than three observation stations are set up at the riverbank and the center of the river channel, with graduated water gauges installed at each station. Simultaneously, video equipment is used to periodically capture images from the water gauges. Water gauge readings are extracted using image recognition algorithms and compared and corrected with data collected by pressure sensors to generate high-precision time-series water level observation data. When collecting data at underwater measuring points, underwater positioning buoys are used to obtain the instantaneous coordinates of the measuring points, and a synchronous clock is used to record the sampling time.

[0016] Based on the sampling time, the water level value at the corresponding moment is retrieved from the observation station data. If necessary, interpolation is used to obtain the corresponding instantaneous water level. Subsequently, a computer program triangulates the coordinates of the underwater measuring point and each observation station, generating a local mesh. The area ratio between the measuring point and adjacent observation stations is calculated based on the area relationships of the triangulated units. When the layout of the observation stations changes, the program automatically reconstructs the mesh and updates the area ratio. Finally, the instantaneous water level of the measuring point is combined with the area ratio, and a weighted calculation is performed to obtain the water level value of the underwater measuring point at the sampling time, thus achieving water level identification.

[0017] It should be added that the water level calculation formula for each measuring point is as follows: ; in, For measuring points water level, For measuring points Record the moment of data collection The water level at each water level station.

[0018] Preferably, step S1 includes the following steps: Step S11: Determine the location of water level observation stations within the target water area and set up three water level observation stations; Step S12: During deployment, determine the spatial coordinates of each water level observation station; Step S13: Continuously monitor each water level observation station in different time periods during the observation period and collect time series data of the corresponding water level values; Step S14: Identify the time series data and perform interpolation or removal processing as needed to obtain the time series water level observation values.

[0019] In one embodiment, three water level observation stations are first deployed at the upstream and downstream locations of the target river section and at the center of the river channel. During deployment, GNSS-RTK positioning is used to accurately measure the water level at each station, and the spatial coordinates of the stations are converted to values ​​in a unified coordinate system. During the observation process, a 10-minute observation cycle is set, and each station automatically collects water level values ​​at preset time points to form continuous time-series data. After data collection is completed, the water level data from different observation stations are uniformly numbered and timestamped for subsequent processing. In the data cleaning stage, if data is missing for certain time periods, linear interpolation is used to supplement it; if obviously abnormal observation values ​​are found, they are removed based on the data patterns of adjacent time periods, ultimately forming a complete time-series water level observation value.

[0020] In another embodiment, three water level observation stations are set up on the left bank, right bank, and downstream outlet of the river within the target water area. During station deployment, a total station combined with an underwater depth sounder is used to determine the coordinates, ensuring that their spatial locations accurately reflect the characteristics of the water area. Each station is equipped with a pressure-type water level gauge, and data is collected every 5 minutes and transmitted back to the central server in real time via a wireless transmission module. The server automatically organizes the data stream into a water level sequence with sampling time stamps and stores it in a database. During data processing, missing data points are repaired by interpolation using historical average trends and nearby times; sudden extreme values ​​are eliminated through threshold filtering and multi-station comparison, thus obtaining time-series water level observation values ​​available for further analysis.

[0021] It should be noted that the number and location of observation stations are not limited to three, and the number of observation stations can be increased or decreased according to the actual water area and accuracy requirements; the observation period can also be flexibly set according to the monitoring task needs, such as 1 minute, 15 minutes or longer; and the data processing methods are not limited to interpolation or rejection.

[0022] Preferably, step S13 includes the following steps: Step S131: During the observation period, the water level sensors of each water level observation station are continuously sampled in different time periods to obtain the corresponding time series water level values; Step S132: Obtain water level images using a camera device installed at the water level observation station; Step S133: Perform image preprocessing on the water gauge image to obtain water level data from the water gauge image; Step S134: Compare the water level data in the water gauge image with the time series water level value. When the difference between the two is within the preset threshold range, use the sensor water level value as the time series data of the corresponding water level value. Step S135: When the difference exceeds the threshold or the sensor data is missing, the time series data and the water level data in the water gauge image are weighted and processed to obtain the time series data of the corresponding water level value.

[0023] In one embodiment, during the observation period, the pressure-type water level sensor at the water level observation station continuously samples at 5-minute intervals to generate time-series water level values. Simultaneously, a camera device deployed at the observation station acquires water level images at the same time intervals. During image acquisition, stable lighting conditions and a fixed shooting angle are maintained to ensure clear visibility of the water level scale. The acquired images undergo preprocessing operations such as grayscale conversion and edge detection to identify the location where the scale lines intersect with the water surface and convert it into corresponding numerical water level data. In the data comparison stage, the water level values ​​recorded by the sensor are compared point-by-point with the water level data obtained from image recognition. When the difference is within a set ±2cm threshold range, the sensor water level value is directly used as the observation result for the corresponding time moment. If the difference exceeds the threshold, or if a sampling point is missing due to sensor malfunction, the sensor water level value and the image-recognized water level value for that moment are weighted and fused, and the result is used as the corresponding time-series water level value.

[0024] In another embodiment, during the observation period, the ultrasonic water level gauge at the water level observation station performs sampling operations every 10 minutes to generate time-series water level values. Simultaneously, a high-definition camera installed near the observation station captures real-time images of the water level gauge. After the images are uploaded to a remote server, a convolutional neural network model automatically identifies the water level scale. The identification result is compared one-to-one with the water level values ​​collected by the sensor. When the difference is less than a set threshold (e.g., 1.5 cm), the sensor water level value is used as the standard time-series data. If the difference is greater than the threshold or the sensor does not generate a valid signal, the two values ​​are input into a fusion calculation module, which outputs a corrected water level value and stores it in a time-series database for subsequent analysis.

[0025] Preferably, step S14 includes the following steps: Step S141: Perform integrity checks on the time-series water level data collected from each water level observation station to determine if there are any missing measurement points; Step S142: Mark the detected missing points and record the missing percentage; Step S143: When the missing measurement ratio is lower than the preset threshold, repair the missing measurement points; Step S144: When the missing measurement ratio exceeds the preset threshold, the observation data for that period is directly removed.

[0026] In one embodiment, when performing integrity checks on the time-series water level data collected from each water level observation station, a database program is first used to iterate through the observation data time by time to determine if there are any null or invalid values. When a missing data point is detected, a missing data marker is automatically generated, and the percentage of missing data points in that time period is calculated. If the missing data percentage is less than 5%, linear interpolation is used for repair, that is, the median value is calculated based on the water level values ​​of two valid times before and after the missing data point, and the result is added to the missing position. If there is data from multiple stations near the missing data point, the water level change trend of neighboring observation stations is further introduced for trend-constrained interpolation to improve the reliability of the repaired value. When the missing data percentage exceeds 5%, the data for that time period is directly removed to avoid large-scale missing data causing deviations in the overall results.

[0027] In another embodiment, a multi-rule approach is used to detect the integrity of time-series water level data. First, missing or delayed data points are identified by comparing timestamp sequences, and the proportion of missing data is recorded for each outlier. When the proportion is less than 10%, a multinomial regression method is used to repair the missing points. This involves fitting and predicting water level data from multiple valid time periods before and after the observation station to fill in the missing points. If video water level data also exists for that time period, the fitting result is weighted and fused with the water level value obtained from image recognition to ensure that the repaired data matches the actual water level. When the proportion exceeds 10%, no further repair is performed; instead, all data for that time period is marked as unusable and removed from subsequent analysis to ensure the accuracy and stability of the identification results.

[0028] Preferably, step S2 includes the following steps: Step S21: Collect the instantaneous spatial coordinates of the underwater measuring point and use them as the spatial positioning parameters of the underwater measuring point; Step S22: Record the sampling time of the underwater measuring point and store the sampling time and the spatial positioning parameters of the underwater measuring point accordingly; Step S23: Compare the sampling time of the underwater measuring point with the time series water level observation values ​​of each water level observation station to determine the two observation times that are closest to the sampling time. Step S24: Calculate the instantaneous water level corresponding to the sampling time based on the water level values ​​at the two observation times before and after, and form the instantaneous water level data of the measuring point.

[0029] In one embodiment, when sampling underwater measuring points, an Acoustic Doppler Current Profiler (ADCP) is used to obtain the instantaneous spatial coordinates of the measuring points. During the acquisition process, the ADCP calculates the depth and horizontal position of the water area where the measuring point is located using real-time acoustic echo signals, and converts the results to a Cartesian coordinate system to ensure consistency with the coordinates of the observation station. Simultaneously, the sampling time of the measuring point is automatically recorded, and the sampling time and the spatial coordinates of the measuring point are stored in a database in a one-to-one correspondence. In subsequent processing, the sampling time is compared with the time series data of the water level observation station, and the program automatically retrieves the two closest consecutive observation times. For example, when the sampling time is 10:07, the observation values ​​at 10:05 and 10:10 are matched as references. Subsequently, the water level values ​​at the two times are proportionally extrapolated using a linear interpolation method to obtain the instantaneous water level of the measuring point at 10:07, which is then used as the standard water level data for that measuring point.

[0030] In another embodiment, the spatial coordinates of the underwater measuring point are obtained through an underwater positioning buoy. The buoy uses underwater acoustic signals to jointly calculate with the GNSS reference station, providing the three-dimensional coordinates of the measuring point at the moment of sampling. The sampling time is uniformly recorded by a high-precision synchronous clock and stored in conjunction with the spatial coordinates. In the water level estimation stage, the sampling time of the measuring point is first read and compared with the time series data of the observation station. When the sampling time and the observation time are not completely consistent, two adjacent moments before and after the sampling time are selected for interpolation estimation. However, unlike the previous embodiment, this embodiment introduces a weighted smoothing algorithm in the interpolation process. That is, the instantaneous water level is calculated based on the relative proportion of the sampling time to the observation time before and after, and a sliding window is used to smooth the water level data of multiple moments before and after to reduce the impact of abrupt changes in the observation data on the results. The final instantaneous water level of the measuring point can reflect the water level status at that moment and has better stability.

[0031] It should be added that the water levels at each water level station at the time of data collection at each measuring point are calculated according to the formula: in Data acquisition and recording time at measurement point n The first time The water level at each water level station , For the time series of water level station observations and The two closest times, , For a certain water level station , The water level at any given time.

[0032] Of particular importance, step S23 includes the following steps: Step S231: Extract the sampling time identifier of the underwater measuring point and obtain the complete time series water level observation data dataset for each water level observation station; Step S232: Compare the sampling time identifier with the observation time in the time series dataset of each water level observation station one by one, and calculate the absolute value of the time difference; Step S233: Sort the calculated time difference values ​​in ascending order and select the two observation times with the smallest time difference as candidate times; Step S234: Determine the positional relationship between the candidate time and the sampling time, and determine the observation time before the sampling time and the observation time after the sampling time to form two observation times.

[0033] In one embodiment, after collecting the sampling time of the underwater measuring points, the program first retrieves the complete time-series water level dataset for each water level observation station from the database. Then, the program compares the sampling time with each observation time in the dataset, calculates the time difference between the two, and takes its absolute value. After all differences are calculated, the results are sorted in ascending order to quickly locate the two observation times closest to the sampling time. Taking a sampling time of 12:07 as an example, if the observation station data are 12:05, 12:10, 12:15, etc., then 12:05 and 12:10 will be selected as candidates. Finally, by comparing the relationship between the candidate times and the sampling time, 12:05, which is before the sampling time, is determined as the previous time, and 12:10, which is after the sampling time, is determined as the subsequent time, thus forming a pair of previous and subsequent observation times, providing a basis for subsequent water level interpolation calculations.

[0034] In another embodiment, after extracting the sampling time and retrieving the time series data from the observation stations, not only is point-by-point time difference calculation performed, but an efficient indexing algorithm is also introduced to accelerate the comparison process. Specifically, the time series data is stored in a balanced binary tree structure according to the timestamp order, and binary search is used to quickly locate the two data points closest to the sampling time. For example, when the sampling time is 09:36, the two times 09:35 and 09:40 are directly retrieved and used as candidate times. Then, based on the comparison between the candidate times and the sampling time, 09:35 is determined as the earlier time and 09:40 as the later time. Unlike the sequential traversal of the previous embodiment, this embodiment shortens the calculation time of the matching process through the index structure, which can significantly improve efficiency when processing large-scale time series data, while ensuring the accuracy of the selected earlier and later observation times.

[0035] Preferably, step S24 includes the following steps: Step S241: Calculate the sampling time and the time interval between two consecutive observation times; Step S242: Determine the relative position of the sampling time between the preceding and following observation times; Step S243: Based on the relative position ratio, perform a weighted calculation on the water level values ​​at the two observation times to obtain the instantaneous water level data of the measuring point.

[0036] In one embodiment, for a given sampling time at a certain measuring point, the records of two water level observation times before and after the sampling time are first obtained, and the actual time interval between the sampling time and the observation times is calculated. For example, if the previous observation time is 10:00 AM, the next observation time is 10:10 AM, and the sampling time is 10:04 AM, then the time interval between the sampling time and the previous time (4 minutes) and the next time (6 minutes) is calculated. Next, the ratio of the sampling time to the observation time is calculated based on the time interval, for example, 4 / (4+6)=0.4. Subsequently, the water level values ​​at the two observation times are linearly weighted according to this ratio. For example, if the water level at the previous time is 2.0 meters and the water level at the next time is 2.2 meters, then the instantaneous water level is 2.0×(1-0.4) + 2.2×0.4 = 2.08 meters, and the result is stored as the instantaneous water level data for the corresponding sampling time at that measuring point for subsequent water level identification and analysis.

[0037] In another embodiment, the processing method for the sampling time at the measuring point is slightly different. First, the water level data of two consecutive water level observation times are automatically retrieved, and the time ratio of the sampling time to the preceding and following observation times is calculated. Then, this ratio is used in the functional module to interpolate the preceding and following water level values ​​to obtain the instantaneous water level data of the measuring point. For example, if the sampling time is exactly between the two observation times, the instantaneous water level is the average of the two water level values; if it is biased towards the preceding observation time, the weight of the preceding water level value is increased accordingly. Finally, this instantaneous water level data is recorded and used to form a complete water level time series at the measuring point.

[0038] Preferably, step S3 includes the following steps: Step S31: Establish the triangulation relationship between the underwater measuring point and the adjacent water level observation station based on the instantaneous spatial coordinates of the underwater measuring point and the spatial location coordinates of the water level observation station; Step S32: Based on the triangulation relationship, calculate the area of ​​the triangle between the underwater measuring point and its adjacent water level observation station; Step S33: Calculate the area ratio between the underwater measuring point and each adjacent water level observation station based on the area of ​​the triangle; Step S34: When the spatial location changes, reconstruct the triangulation relationship; Step S35: Under the reconstructed triangulation relationship, update the area ratio between the underwater measuring point and the adjacent water level observation station.

[0039] In one embodiment, the instantaneous spatial coordinates of the underwater measuring point and the fixed spatial coordinates of each water level observation station are first obtained. Based on these coordinates, the three nearest water level observation stations around the measuring point are automatically identified as vertices for triangulation. Subsequently, a computer program generates triangular units containing the underwater measuring point using a triangulation algorithm (e.g., the Delaunay triangulation algorithm). Based on the generated triangulation structure, the area of ​​each triangular unit is calculated, thus obtaining the area value between the measuring point and each adjacent water level observation station. Next, the area ratio between the underwater measuring point and each adjacent water level observation station is calculated by comparing the area of ​​each individual triangle with the total area. If the position of the water level observation station or measuring point changes, a reconstruction mechanism is triggered, automatically regenerating the triangulation structure and updating the area ratio to ensure the accuracy of subsequent water level calculations.

[0040] In another embodiment, the spatial coordinates of the underwater measuring point and the water level observation station are also input into the triangulation module. This module determines the vertices of the triangle formed by the coordinates of the surrounding water level observation stations and calculates the area of ​​the triangle using software. Subsequently, an area ratio method is used to weight the spatial location of the measuring point relative to the triangle vertices to reflect the spatial influence of the measuring point relative to each water level observation station. If the spatial location or measuring point is adjusted, the module automatically reconstructs the triangulation and recalculates the area ratio of each measuring point to its adjacent water level observation station, forming area weight data that can be directly used for water level calculation.

[0041] It should be added that the area between the measuring point and the adjacent water level station is calculated using the following formula: Among them, measuring points and respectively , For measuring points coordinates , , Water level stations and water level station The coordinates.

[0042] Preferably, step S3 includes the following steps: Step S311: Based on the instantaneous spatial coordinates of the underwater measuring point and the spatial coordinates of the water level observation station, determine the water level observation station adjacent to the location of the underwater measuring point; Step S312: Combine the coordinates of the underwater measuring point and the coordinates of the adjacent water level observation station to form the partition vertices; Step S313: Based on the partitioned vertices, generate triangular units containing underwater measuring points according to the preset triangulation rules; Step S314: Connect the triangular units to form a triangular partition relationship.

[0043] In one embodiment, the instantaneous spatial coordinates of the underwater measuring point and the spatial coordinates of all water level observation stations are first input into the calculation module. Based on the distance relationship between the measuring point and each observation station, the module automatically selects three water level observation stations closest to the underwater measuring point as adjacent vertices for triangulation. Then, the coordinates of the underwater measuring point and these three observation station coordinates are combined to form a set of triangulation vertices. Based on this, triangular units containing the underwater measuring point are generated according to a preset triangulation rule (such as connecting adjacent vertices clockwise to form triangles). Finally, the generated triangular units are connected sequentially to form a complete triangulation structure, providing a spatial basis for subsequent area ratio calculations.

[0044] In another embodiment, a software module receives the spatial coordinates of underwater measuring points and water level observation stations, and determines which water level observation stations form triangle vertices with the measuring points based on spatial proximity. After combining the measuring point coordinates with the coordinates of adjacent observation stations, a triangular unit containing the measuring point is generated according to a custom triangulation rule (e.g., ensuring the minimum angle of the triangle is not lower than a set threshold). Then, the module connects the generated triangular units topologically to form a complete triangulation structure, so that the area ratio between each measuring point and adjacent water level observation stations can be calculated in subsequent steps.

[0045] Preferably, step S33 includes the following steps: Step S331: Calculate the area of ​​each triangle formed by the underwater measuring point and the adjacent water level station; Step S332: Calculate the sum of the areas of all triangles, which is the total area; Step S333: Calculate the ratio of the area of ​​a single triangle to the total area to obtain the area ratio.

[0046] In one embodiment, the coordinates of the underwater measuring point and its adjacent water level observation stations are first input into the area calculation module. The module calculates the area of ​​each triangular unit sequentially according to the established triangulation relationship, typically using the cross product formula with vertex coordinates. Then, the areas of all triangles are summed to obtain the total area of ​​the triangles surrounding the underwater measuring point. Finally, the area of ​​each individual triangle is compared to the total area to generate the area ratio between the measuring point and each adjacent water level observation station, which is used for subsequent weighted water level calculations.

[0047] In another embodiment, the module first identifies triangular units formed by the underwater measuring point and adjacent water level observation stations. Then, the area of ​​each triangle is determined numerically, for example, using the coordinate difference method or Heron's formula. After summing the areas of all triangles to obtain the total area, the module divides the area of ​​each triangle by the total area to obtain a standardized area ratio. This area ratio reflects the spatial weight between the measuring point and each adjacent water level observation station, providing basic data for the weighted calculation of the water level at the measuring point.

[0048] Preferably, step S35 includes the following steps: Step S351: When spatial water level changes cause distortion, a re-determination of spatial positional relationships is triggered; Step S352: Perform time-densified data acquisition on water level observations, and obtain dense time-series water level data by increasing the sampling frequency per unit time. Step S352: Smooth the encrypted water level data by using a sliding window method to calculate the average value of a certain number of continuous observations to obtain the smoothed water level sequence; Step S354: Based on the smoothed water level sequence, reconstruct the triangulation relationship between underwater measuring points and adjacent water level stations; Step S355: Update the area ratio between the underwater measuring point and the adjacent water level observation station.

[0049] In one embodiment, when abnormal fluctuations in water level changes are detected or significant deviations occur in the water level calculation at the measuring points, a re-determination process of spatial location relationships is triggered. At this time, the water level observation module increases the data sampling frequency, acquiring more observation values ​​from the water level observation stations per unit time, thereby generating high-density time series data. Subsequently, a sliding window algorithm is used to smooth the densely collected data, for example, by calculating the average value of five consecutive observation points to form a smoothed water level sequence. Based on this smoothed sequence, the triangulation relationship between the underwater measuring points and adjacent water level observation stations is reconstructed, and the area ratio between each measuring point and adjacent water level observation stations is recalculated for subsequent weighted water level calculations.

[0050] In another embodiment, when water level observations detect a difference between the water level value at a local measuring point and the overall water area trend exceeding a set threshold, a dynamic adjustment mode is automatically activated. By increasing the sampling frequency and shortening the water level observation interval, denser data points are obtained. For the acquired dense data sequence, a moving average or weighted smoothing algorithm is used to remove transient interference and noise, resulting in a stable water level sequence. Subsequently, the spatial distribution relationship between underwater measuring points and adjacent observation stations is re-analyzed, a new triangulation grid is constructed, and the area ratio corresponding to each triangle is updated to ensure accurate and reliable spatial weighted calculation of the water level at the measuring points.

[0051] Of particular importance, step S4 includes the following steps: Step S41: Obtain the instantaneous water level values ​​of each adjacent water level observation station corresponding to the underwater measuring point, and extract the corresponding area ratio weighting coefficient; Step S42: Multiply the instantaneous water level values ​​of each adjacent water level observation station with the corresponding area ratio weighting coefficient to obtain the weighted water level value of each station; Step S43: Sum the weighted water level values ​​of each station to obtain the comprehensive water level value of the underwater measuring point at the sampling time; Step S44: Compare and analyze the comprehensive water level value with the preset water level identification standard to complete the water level identification of the underwater measuring point.

[0052] In one embodiment, after obtaining the sampling time of the underwater measuring point, the instantaneous water level values ​​of multiple water level observation stations adjacent to the measuring point are automatically read. For example, if the measuring point is located in the confluence area of ​​two rivers, the real-time water level readings of the three adjacent observation stations are extracted. Simultaneously, based on the regional hydrological characteristics and the relative positional relationship between the measuring point and each observation station, the area ratio weighting coefficient corresponding to each observation station is calculated. Subsequently, the instantaneous water level value of each observation station is multiplied by its weighting coefficient one by one to form a weighted water level value.

[0053] Taking three observation stations as an example, assuming the water levels are 1.25m, 1.40m, and 1.32m, with weighting coefficients of 0.3, 0.5, and 0.2, the corresponding weighted water level values ​​are 0.375m, 0.700m, and 0.264m. Next, these three values ​​are added together to obtain 1.339m, which is the comprehensive water level value at the sampling time for that observation point. Finally, this comprehensive water level value is compared with a preset water level identification standard, such as whether it exceeds a certain flood warning threshold, thereby completing the identification of the water level status at that underwater observation point.

[0054] In another embodiment, when calculating water levels, in addition to using area ratio weights, a dynamic correction factor is incorporated to optimize the weighting results. This correction factor is automatically adjusted based on historical monitoring data and current meteorological conditions. For example, when there are significant differences in water level change trends between adjacent observation stations, the weight of observation stations with hydrological characteristics closer to the measurement point location is increased, while the weight of other observation stations is decreased, thereby avoiding errors caused by local anomalies.

[0055] Taking a specific monitoring session as an example, the instantaneous water levels at the three observation stations were 1.10m, 1.35m, and 1.50m, with initial weights of 0.4, 0.4, and 0.2. However, because the water level fluctuation at the third station was significantly greater than that at the other two stations, the weights were automatically adjusted to 0.45, 0.45, and 0.1. After weighted calculation, the comprehensive water level value at the sampling time was obtained as 1.29m. Subsequently, this value was compared with different levels of water level standards in the database, such as normal water level, warning water level, and guaranteed water level, and the monitoring point was automatically identified as being close to the warning water level.

[0056] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A water level calculation method based on triangular network area weighting, characterized in that, Includes the following steps: Step S1: Deploy multiple water level observation stations and record the spatial coordinates of each station; obtain the time series water level observation values ​​of each station within the observation period. Step S2: Collect the instantaneous coordinates and sampling time of the underwater measuring point, and extract the corresponding instantaneous water level from the time series water level observations based on the sampling time; Step S3: Establish a triangulation relationship based on the spatial location of underwater measuring points and water level observation stations, calculate the area ratio between underwater measuring points and adjacent water level observation stations, and automatically reconstruct the triangulation relationship and update the area ratio when the number and location of water level observation stations change. Step S4: Calculate and process the extracted instantaneous water level combined with the area ratio to obtain the water level value of the underwater measuring point at the sampling time, thereby identifying the water level.

2. The water level calculation method based on triangular network area weighting according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Determine the location of water level observation stations within the target water area and set up three water level observation stations; Step S12: During deployment, determine the spatial coordinates of each water level observation station; Step S13: Continuously monitor each water level observation station in different time periods during the observation period and collect time series data of the corresponding water level values; Step S14: Identify the time series data and perform interpolation or removal processing as needed to obtain the time series water level observation values.

3. The water level calculation method based on triangular network area weighting according to claim 2, characterized in that, Step S13 includes the following steps: Step S131: During the observation period, the water level sensors of each water level observation station are continuously sampled in different time periods to obtain the corresponding time series water level values; Step S132: Obtain water level images using a camera device installed at the water level observation station; Step S133: Perform image preprocessing on the water gauge image to obtain water level data from the water gauge image; Step S134: Compare the water level data in the water gauge image with the time series water level value. When the difference between the two is within the preset threshold range, use the sensor water level value as the time series data of the corresponding water level value. Step S135: When the difference exceeds the threshold or the sensor data is missing, the time series data and the water level data in the water gauge image are weighted and processed to obtain the time series data of the corresponding water level value.

4. The water level calculation method based on triangular network area weighting according to claim 2, characterized in that, Step S14 includes the following steps: Step S141: Perform integrity checks on the time-series water level data collected from each water level observation station to determine if there are any missing measurement points; Step S142: Mark the detected missing points and record the missing percentage; Step S143: When the missing measurement ratio is lower than the preset threshold, repair the missing measurement points; Step S144: When the missing measurement ratio exceeds the preset threshold, the observation data for that period is directly removed.

5. The water level calculation method based on triangular network area weighting according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Collect the instantaneous spatial coordinates of the underwater measuring point and use them as the spatial positioning parameters of the underwater measuring point; Step S22: Record the sampling time of the underwater measuring point and store the sampling time and the spatial positioning parameters of the underwater measuring point accordingly; Step S23: Compare the sampling time of the underwater measuring point with the time series water level observation values ​​of each water level observation station to determine the two observation times that are closest to the sampling time. Step S24: Calculate the instantaneous water level corresponding to the sampling time based on the water level values ​​at the two observation times before and after, and form the instantaneous water level data of the measuring point.

6. The water level calculation method based on triangular network area weighting according to claim 4, characterized in that, Step S24 includes the following steps: Step S241: Calculate the sampling time and the time interval between two consecutive observation times; Step S242: Determine the relative position of the sampling time between the preceding and following observation times; Step S243: Based on the relative position ratio, perform a weighted calculation on the water level values ​​at the two observation times to obtain the instantaneous water level data of the measuring point.

7. The water level calculation method based on triangular network area weighting according to claim 1, characterized in that, Step S3 includes the following steps: Step S31: Establish the triangulation relationship between the underwater measuring point and the adjacent water level observation station based on the instantaneous spatial coordinates of the underwater measuring point and the spatial location coordinates of the water level observation station; Step S32: Based on the triangulation relationship, calculate the area of ​​the triangle between the underwater measuring point and its adjacent water level observation station; Step S33: Calculate the area ratio between the underwater measuring point and each adjacent water level observation station based on the area of ​​the triangle; Step S34: When the spatial location changes, reconstruct the triangulation relationship; Step S35: Under the reconstructed triangulation relationship, update the area ratio between the underwater measuring point and the adjacent water level observation station.

8. The water level calculation method based on triangular network area weighting according to claim 7, characterized in that, Step S31 Includes the following steps: Step S311: Based on the instantaneous spatial coordinates of the underwater measuring point and the spatial coordinates of the water level observation station, determine the water level observation station adjacent to the location of the underwater measuring point; Step S312: Combine the coordinates of the underwater measuring point and the coordinates of the adjacent water level observation station to form the partition vertices; Step S313: Based on the partitioned vertices, generate triangular units containing underwater measuring points according to the preset triangulation rules; Step S314: Connect the triangular units to form a triangular partition relationship.

9. The water level calculation method based on triangular network area weighting according to claim 7, characterized in that, Step S33 includes the following steps: Step S331: Calculate the area of ​​each triangle formed by the underwater measuring point and the adjacent water level station; Step S332: Calculate the sum of the areas of all triangles, which is the total area; Step S333: Calculate the ratio of the area of ​​a single triangle to the total area to obtain the area ratio.

10. The water level calculation method based on triangular network area weighting according to claim 7, characterized in that, Step S35 includes the following steps: Step S351: When spatial water level changes cause distortion, a re-determination of spatial positional relationships is triggered; Step S352: Perform time-densified data acquisition on water level observations, and obtain dense time-series water level data by increasing the sampling frequency per unit time. Step S352: Smooth the encrypted water level data by using a sliding window method to calculate the average value of a certain number of continuous observations to obtain the smoothed water level sequence; Step S354: Based on the smoothed water level sequence, reconstruct the triangulation relationship between underwater measuring points and adjacent water level stations; Step S355: Update the area ratio between the underwater measuring point and the adjacent water level observation station.

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