A processing method for converting multi-source heterogeneous river section data into MIKE model

Abstract

The application provides a processing method for converting multi-source heterogeneous river cross-section data into a MIKE model, which comprises the following steps: obtaining multi-source heterogeneous river cross-section data; comparing the river cross-section data with a preset data template to determine a format type; performing abnormality checking and processing on the river cross-section data; extracting target data fields and performing standardization processing according to data requirements of the MIKE model; performing merging processing on the river cross-section data belonging to the same river cross-section; converting the river cross-section data into an elevation datum used for calculation of the MIKE model; identifying characteristic points of the river cross-section according to a storage sequence of cross-section measuring points and elevation data; calculating roughness parameters of the river cross-section according to geomorphologic feature description of the cross-section measuring points; and arranging the river cross-section data and corresponding characteristic points and roughness parameters into a cross-section data format required by the MIKE model. The application can solve the technical problem of efficiently and accurately importing multi-source heterogeneous river cross-section data into the MIKE model.

Description

Technical Field

[0001] This invention relates to the field of water conservancy information technology and hydrodynamic model preprocessing technology, specifically to a method for converting multi-source heterogeneous river cross-section data into a MIKE model. Background Technology

[0002] The MIKE model is a leading international numerical simulation software developed by the Danish Hydraulics Institute (DHI). It is widely used in simulations of hydrodynamics, water quality, and sediment transport in water bodies such as rivers, lakes, and oceans. River cross-section data is one of the fundamental input data for building the MIKE model, and its data quality and processing efficiency directly affect the model's building speed and computational accuracy.

[0003] However, in actual engineering projects, river cross-section data comes from diverse sources, including historical survey data, digitized design drawings, lidar point cloud data, and spreadsheets provided by different departments. This data is often stored in various file formats such as ".txt", ".csv", and ".xls", and its internal data structures (such as coordinate systems, elevation datums, data arrangement order, and attribute field definitions) vary greatly, exhibiting typical multi-source heterogeneous characteristics. For a long time, converting this data into the specific cross-section format required by the MIKE model has mainly relied on manual verification, format adjustment, and the writing of scattered scripts. When the number of cross-sections is large, this traditional processing method is not only inefficient and time-consuming, but also highly susceptible to data errors due to human error, such as misaligned mileage, inconsistent elevation datums, and deviations in thalweg point identification. These problems are often difficult to detect during the model calculation stage, seriously affecting the reliability and efficiency of the model.

[0004] Therefore, there is an urgent need for a standardized, highly automated, and universal processing method to solve the technical challenge of efficiently and accurately importing multi-source heterogeneous river cross-section data into the MIKE model. Summary of the Invention

[0005] The purpose of this invention is to provide a method for converting multi-source heterogeneous river cross-section data into a MIKE model, aiming to solve the technical problems of low efficiency, error susceptibility, and insufficient automation in the processing of multi-source heterogeneous river cross-section data in existing technologies. The specific technical solution is as follows: A method for converting multi-source heterogeneous river cross-section data into a MIKE model includes: Obtain a set A consisting of multi-source heterogeneous river cross-section data; The structural features of the river cross-section data in set A are compared with the structural features of the preset data template to determine the format type of the river cross-section data. Based on the data template corresponding to the river cross-section data, anomaly checks and processing are performed on the river cross-section data; According to the data requirements of the MIKE model, target data fields are extracted from the river cross-section data, and set B is obtained after standardizing the target data fields; The data of river cross sections belonging to the same river cross section in set B are merged to obtain set C; The river cross-section data in set C are converted into the elevation datum used in the MIKE model calculation to obtain set D; Based on the storage order of the cross-section measurement points and elevation data in set D, identify the characteristic points of the river channel cross-section; Based on the geomorphic feature description of the cross-section measuring points in set D, determine the roughness value of each cross-section measuring point, and calculate the roughness parameter of the river channel cross-section; The river cross-section data in set D, along with the corresponding feature points and roughness parameters, are organized into the cross-section data format required by the MIKE model.

[0006] Preferably, the format type of the river cross-section data is determined as follows: Extract the structural feature vectors of the river cross-section data and each data template; Adopting the first The structural feature vector of the first river cross-section data and the first Weighted Euclidean distance between the structural feature vectors of each data template To measure the similarity between the two; The calculated weighted Euclidean distances are sorted in ascending order. ,calculate and The relative distance between ; like Then the first The data of each river cross section were directly matched using a weighted Euclidean distance. The format type of the corresponding data template; if Then the first The data from individual river cross-sections were initially matched using weighted Euclidean distance. The format type of the corresponding data template is displayed, and a manual review is prompted; if Then it is considered that the first No matching data template was found for the river cross-section data; in, This indicates the total number of preset data templates. , This represents the data of any river cross-section in set A.

[0007] Preferably, anomaly checks and processing are performed on the river cross-section data, specifically: Data missing detection and handling: For each cross-section measurement point record, check for empty or missing values ​​in the fields of river name, river cross-section number, cross-section mileage location, starting distance, and elevation. If the river name, river cross-section number, or cross-section mileage location field is missing, the processing flow for that river cross-section is suspended and marked as awaiting manual entry. If the starting distance or elevation field is missing, the corresponding cross-section measurement point is removed and recorded. Data type checking and processing: The starting distance and elevation fields are parsed as floating-point numbers using a forced type conversion method. If the parsing fails, it is judged as a type anomaly and the corresponding cross-section measurement points are removed. If the number of cross-section measurement points with type anomalies in a certain river cross-section data exceeds the preset proportion of the total number of cross-section measurement points in the river cross-section data, the subsequent processing of the river cross-section is suspended and transferred to manual review. Error character detection and handling: Illegal characters are identified and cleaned up using regular expression whitelist filtering. Full-width numbers and letters are automatically mapped to half-width characters. If a cell is empty after cleaning, it is marked as a missing value and transferred to data missing detection and handling. Elevation data outlier detection and handling: An elevation outlier is determined using a statistical threshold-based method. When the elevation value of a cross-section measuring point is outside the range of absolute median difference that is a preset multiple of the median of all measuring points in the river cross-section, the measuring point is determined to be an elevation outlier. For the cross-section measuring points determined to be elevation outliers, their elevation is corrected using linear interpolation.

[0008] Preferably, the data of river cross-sections belonging to the same river cross-section in set B are merged, specifically: When there are two or more river cross-section data in set B with completely identical river names and river cross-section numbers, it is determined that these river cross-section data belong to the same wide cross-section and are classified into the same candidate group. The data of each river section within the same candidate group are sorted in ascending order of distance from the starting point to determine the left-right positional relationship of each river section data on the actual riverbed. After sorting, two adjacent river section data are subjected to a dual-condition judgment of spatial continuity and elevation consistency. If the dual-condition judgment is satisfied, the two adjacent river section data are merged into the same section data in a head-to-tail manner. The merged section data and the next adjacent river section data continue to be subjected to dual-condition judgment and merging processing, and so on, until all river section data in the candidate group are processed. If the spatial continuity or elevation consistency conditions of two adjacent river section data are not met, the merging process will be terminated, and an alarm will be triggered according to the type of condition that is not met.

[0009] Preferably, a dual-condition judgment is made on the spatial continuity and elevation consistency of two adjacent river section data after sorting, specifically: Spatial continuity determination: For two adjacent river cross-sections after sorting, the cross-section in the preceding sequence is denoted as segment A, and the cross-section in the following sequence is denoted as segment B. The endpoint of segment A is the cross-section measuring point with the largest starting-to-start distance within that segment, and the starting endpoint of segment B is the cross-section measuring point with the smallest starting-to-start distance within that segment. The spatial distance between the endpoint of segment A and the starting endpoint of segment B is then calculated. ;like If it is determined to be spatially continuous; If it is determined to be quasi-continuous; This is determined to be a spatial discontinuity; Elevation consistency determination: When When calculating the elevation difference between the end point of segment A and the beginning point of segment B, directly calculate the absolute value of the difference. ;when At that time, linear extrapolation was performed based on the measuring points at the last two sections of segment A and the first two sections of segment B to obtain extrapolated elevation values. The absolute value of the difference between the two extrapolated elevation values ​​was then calculated. ;like If the elevation is consistent, it is determined that the elevation is consistent; This was determined to be due to inconsistent elevations; Comprehensive judgment: When the spatial continuity judgment result is spatial continuity or quasi-continuity, and the elevation consistency judgment result is elevation consistency, then the dual condition judgment is satisfied; otherwise, the dual condition judgment is not satisfied. in, , and All of these are judgment thresholds.

[0010] Preferably, the characteristic points for identifying the river channel cross-section include the thalweg point, the left bank levee point, the right bank levee point, the left bank beach-channel boundary point, and the right bank beach-channel boundary point.

[0011] Preferably, the roughness value of each cross-section measuring point is determined based on the geomorphic feature description of the cross-section measuring points in set D, and the roughness parameter of the river channel cross-section is calculated, specifically: Based on the geomorphic features of each cross-section measuring point, the roughness value of each cross-section measuring point is determined by referring to the preset roughness value table. The roughness parameter of the river channel cross-section is the overall roughness of the river channel cross-section. The roughness values ​​of each cross-section measuring point are weighted and averaged to obtain the overall roughness of the river channel cross-section.

[0012] Preferably, the roughness value of each cross-section measuring point is determined based on the geomorphic feature description of the cross-section measuring points in set D, and the roughness parameter of the river channel cross-section is calculated, specifically: Based on the geomorphic features of each cross-section measuring point, the roughness value of each cross-section measuring point is determined by referring to the preset roughness value table. Using the identified thalassium point, the boundary between the left bank beach and the right bank beach, the river cross section is divided into multiple roughness zones. Using the representative width of each cross-sectional measuring point within the roughness zone as the weight, the roughness values ​​of each cross-sectional measuring point within the roughness zone are weighted and averaged to obtain the comprehensive roughness of the roughness zone. The physical rationality and spatial consistency of the comprehensive roughness of each roughness zone of the river section are checked. If any roughness zone of a river section fails any check, the processing of that river section is stopped and the river section is marked as awaiting manual review.

[0013] Preferably, the river channel cross-section is divided into multiple roughness zones using the identified thalweg point, the left bank floodplain-channel boundary point, and the right bank floodplain-channel boundary point. Specifically: The river channel is divided into the left bank floodplain area, the main channel area, and the right bank floodplain area, with the boundary between the left bank floodplain and the right bank floodplain as the boundary. Further subdivision of the main tank area: Using the thalweg point as a reference, the curvature of each cross-sectional measuring point within the main channel area is calculated point by point. The location with the largest absolute value of curvature within the main channel area to the left of the thalweg point is selected as the dividing point between the left side slope area and the main channel thalweg area. Within the main channel region to the right of the thalweg point, the location with the largest absolute value of curvature is selected as the dividing inflection point between the right-side main channel slope area and the main channel thalweg area. Through the dividing inflection point and The main channel area is further subdivided into the left main channel slope area, the main channel deep channel area, and the right main channel slope area; Further subdivision of the left and right shoal areas: Starting from the boundary point between the river channel and the floodplain area that needs to be subdivided, calculate the single-step elevation rise between adjacent cross-sectional measuring points point by point in the direction away from the main channel area; if a certain cross-sectional measuring point If the elevation rise in two or more consecutive steps exceeds the preset threshold, then... Then and subsequent continuous single-step elevation rise exceeding the preset threshold The cross-sectional measuring points are recorded as sequence P; the first cross-sectional measuring point in sequence P is... This point was identified as a candidate dividing point. Obtain geomorphic feature descriptions of candidate boundary points and their adjacent cross-sectional measuring points. If the geomorphic features at the candidate boundary point change in type compared to the geomorphic features of the adjacent cross-sectional measuring points on the side closer to the main channel area, then the cross-validation is passed, and the candidate boundary point is determined as the boundary point between the near-channel beach and the far-channel high beach. The beach area that needs to be subdivided is further subdivided into the near-channel beach area and the far-channel high beach area through the beach boundary point. If cross-validation fails, the next cross-sectional measurement point in sequence P is selected as a new candidate boundary point for cross-validation again until cross-validation passes or sequence P is traversed. If no cross-sectional measurement point passes cross-validation after sequence P is traversed, the first identified candidate boundary point is used as the beach boundary point, and a prompt message is generated for manual confirmation.

[0014] Preferably, the physical rationality check is as follows: if the overall roughness of a certain roughness zone in the river cross section exceeds its corresponding reasonable value range, or if the relative relationship between the overall roughness of each roughness zone violates the preset physical law, then the physical rationality check of the river cross section fails. Spatial consistency check: Calculate the comprehensive relative change rate of roughness of the same type of roughness partitions in adjacent river sections. If the comprehensive relative change rate of roughness of the same type of roughness partitions in two adjacent river sections exceeds the preset threshold, then mark the combination of adjacent river sections as failing the spatial consistency check.

[0015] The application of the technical solution of the present invention has the following beneficial effects: This invention constructs a fully automated processing method from data import, format recognition, anomaly detection to feature analysis and model output. It breaks through the inefficient mode of manual processing of multi-source cross-sectional data line by line, which can greatly improve work efficiency and effectively reduce the error rate in the manual processing process.

[0016] This invention automatically determines the format type of imported cross-sectional data by constructing a multi-dimensional feature vector template matching algorithm. It also has anomaly detection functions such as missing data, data type mismatch, and erroneous characters. It identifies and processes abnormal values ​​caused by cross-sectional measurement errors, so that the cross-sectional data reflects the real river channel topographic changes and enhances the stability of subsequent river channel cross-sectional feature point identification.

[0017] This invention proposes an automatic identification and merging mechanism for wide cross-sections. When the river name and river cross-section number of multiple cross-section records are consistent, it is automatically identified as a wide cross-section and merged head to tail according to the spatial position. At the same time, it performs intelligent judgment based on two conditions: spatial continuity and elevation consistency. When there is a gap at the head to tail, it performs interpolation processing to ensure the integrity and continuity of the cross-sectional shape of the wide river channel.

[0018] This invention can automatically analyze and identify key feature points of a cross-section, such as the thalweg point, the left bank levee point, the right bank levee point, the left bank beach-channel boundary point, and the right bank beach-channel boundary point. Based on the geomorphological features of the cross-section points, it can automatically determine the roughness of each cross-section point and calculate the comprehensive roughness of the cross-section by weighting and summing according to the representative width, thus providing accurate riverbed resistance parameters for the MIKE model.

[0019] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0020] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of the method for converting multi-source heterogeneous river cross-section data into a MIKE model in Example 1; Figure 2 This is a schematic diagram of feature point recognition in Example 1. Detailed Implementation

[0021] To facilitate understanding of the present invention, a more complete description is provided below, along with preferred embodiments. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the present invention.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

[0023] Example 1: See Figure 1 This embodiment provides a method for converting multi-source heterogeneous river cross-section data into a MIKE model, including the following steps: S1. Obtain a set A consisting of multi-source heterogeneous river cross-section data; S2. Compare the structural features of the river cross-section data in set A with the structural features of the preset data template to determine the format type of the river cross-section data; S3. Based on the data template corresponding to the river cross-section data, perform anomaly checks and processing on the river cross-section data; S4. Extract the target data fields from the river cross-section data according to the data requirements of the MIKE model, and obtain set B after standardizing the target data fields; S5. Merge the river cross-section data belonging to the same river cross-section in set B to obtain set C; S6. Convert the river cross-section data in set C into the elevation datum used for MIKE model calculations to obtain set D; S7. Identify the characteristic points of the river channel cross-section based on the storage order of the cross-section measurement points and the elevation data in set D. S8. Determine the roughness value of each cross-section measuring point based on the geomorphic feature description of the cross-section measuring points in set D, and calculate the roughness parameter of the river channel cross-section. S9. Organize the river cross-section data in set D, along with the corresponding feature points and roughness parameters, into the cross-section data format required by the MIKE model.

[0024] The processing method of this embodiment will be described in detail below: Preferably, in this embodiment, river cross-section data in conventional file formats such as .txt, .csv, and .xls are imported in batches to obtain multi-source heterogeneous river cross-section data. After the data is acquired, it is stored in a database to achieve centralized data management and efficient subsequent retrieval, providing a unified data foundation for subsequent processing.

[0025] Preferably, in order to determine the format type of the acquired river cross-section data, this embodiment pre-sets several data templates. By comparing a single river cross-section data with the pre-set data templates, the format type of the river cross-section data is determined. In this embodiment, the format type of the river cross-section data is determined as follows: Extract the structural feature vectors of the river cross-section data and each data template; Adopting the first The structural feature vector of the first river cross-section data and the first Weighted Euclidean distance between the structural feature vectors of each data template To measure the similarity between the two; The calculated weighted Euclidean distances are sorted in ascending order. ,calculate and The relative distance between ; like Then the first The data of each river cross section were directly matched using a weighted Euclidean distance. The format type of the corresponding data template; if Then the first The data from individual river cross-sections were initially matched using weighted Euclidean distance. The corresponding data template format type will be displayed, and a manual review will be prompted. The automated conversion process for this data will be paused until the review is passed. Then it is considered that the first If no matching data template is found for a river section, a prompt will appear indicating that a new data template needs to be created, and the matching will be performed again after the data template is created. Preferred, the first The structural feature vector of the first river cross-section data and the first The weighted Euclidean distance between the structural feature vectors of the data templates is expressed as: in, , , Indicates the first The structural feature vector of the first river cross-section data and the first The weighted Euclidean distance between the structural feature vectors of the data templates This represents the total number of dimensions of the structural feature vectors. Indicates the first Weights of each dimension Indicates the first The data for the first river cross section were in the [number]th [section]. Feature values ​​in each dimension Indicates the first The data template in the first Feature values ​​in each dimension This represents the total number of river cross-section data in set A. This indicates the total number of preset data templates.

[0026] Preferably, the relative distance ratio Represented as: Preferably, the structural feature vector in this embodiment includes seven dimensions of features: metadata independent storage flag, keyword flag, number of data columns, data column name features, average number of fields per data row, null value rate, and data arrangement pattern. The value is 7, and in this embodiment, the weights of each dimension are set to 0.1, 0.4, 0.2, 0.3, 0.1, 0.1, and 0.1, respectively.

[0027] Specifically, the values ​​for the seven dimensions of features in this embodiment are determined as follows: (1) Metadata independent storage flag (value range is 0 or 1): detects the data file (referring to data template or river cross-section data) before The value is 1 if the row independently contains metadata fields for elevation datum or coordinates, and 0 if it contains one or more of these metadata fields. Take 20.

[0028] (2) Keyword flag (value range is 0 or 1): Check whether the data file contains four target keywords: river name, cross-section mileage, starting distance, and elevation. If all four are included, the value is 1; otherwise, the value is 0.

[0029] (3) Number of data columns (integers ranging from 2 to 20): Before reading the data file The row represents the maximum number of columns after being separated by the field separator. River cross-section data should include at least two columns: distance from the starting point and elevation, with a minimum value of 2. Since the main information generally does not exceed 20 categories, the maximum value is 20, as per this embodiment. Take 20.

[0030] (4) Data column name characteristics (integers ranging from 1 to 524288): Each column name is matched and coded according to a preset coding rule. The sum of all matched column name codes is used as the feature value of that dimension. The coding rule is as follows: starting distance is coded as 1, elevation is coded as 2, river name is coded as 4, cross-section mileage is coded as 8, river cross-section number is coded as 16, and remark is coded as 32, and so on. Since each code is a power of 2, no single code is equal to any combination of other codes. Therefore, the column name combination can be uniquely deduced from the final code value.

[0031] (5) Average number of fields per row (floating-point number ranging from 2 to 20): This measures the number of fields in each row of all data rows in the statistical data file. The average number of fields per row is used as the value for this dimension. This indicator reflects the completeness of the data. If the average value is significantly less than the number of data columns, it indicates that there are many missing values ​​in the data. For example, if there are 8 rows of data in the river section data area, each row has 4 fields (serial number, distance from starting point, elevation, and remarks), and there is no missing data, then the average number of fields per row is (4×8) / 8=4.

[0032] (6) Null Value Rate (a floating-point number ranging from 0 to 1): The total number of data cells in the statistical data file (including the metadata area and the measurement point data area), plus the number of null or missing values, is calculated using the following formula: Null Value Rate = (Number of null cells + Number of missing value cells) / Total number of data cells. This indicator reflects the completeness of the data. The closer the null value rate is to 0, the more complete the data; the closer it is to 1, the more severe the data loss.

[0033] (7) Data arrangement mode (integers ranging from 0 to 3): determined according to the arrangement of data in the data file. The encoding rules are as follows: 0 indicates one cross-section point per row, 1 indicates one complete cross-section per row, 2 indicates matrix arrangement (all cross-sections share the same set of starting distance sequences (the horizontal coordinate is fixed), and each cross-section only stores the elevation sequence. That is, the starting distance is used as the column name, and the elevation of each cross-section is arranged in a two-dimensional matrix by row), and 3 indicates other arrangement methods.

[0034] Preferably, those skilled in the art can set data templates according to the industry's conventional expression formats. In this embodiment, two commonly used data template formats are listed in Tables 1 and 2: Table 1. First type of data template Table 2. Second type of data template Preferably, to comprehensively detect various quality issues in the river cross-section data and ensure the accuracy of subsequent processing results, this embodiment performs anomaly checks and processing on the river cross-section data according to the data template corresponding to the river cross-section data. Specifically, based on the data template corresponding to the format type determined in step S2, the position information of the column where each target field is located is obtained, and anomaly checks and processing are performed on the corresponding fields accordingly. Specifically, the anomaly checks and processing performed on the river cross-section data include data missingness checks and processing, data type checks and processing, erroneous character checks and processing, and elevation data outlier value checks and processing.

[0035] Preferably, the data missing detection and processing includes: For each cross-section measurement point record, the fields for river name, river cross-section number, cross-section mileage location, starting distance, and elevation are checked for empty or missing values. The detection method is to scan row by row and column by column to identify completely empty cells (empty strings or null), predefined placeholders (such as "NULL", "N / A", "None", etc.). Errors include blank strings (e.g., strings with a length of 0 after processing by Python's built-in strip function) and missing numerical markers in river cross-section data (e.g., Excel's #N / A, #VALUE!, etc.).

[0036] If the river name, river section number, or section mileage location fields are missing, the entire river section system is unusable. Subsequent processing of the river section is suspended, its status is marked as awaiting manual input, and the name and location of the missing fields are recorded. If the starting distance or elevation field is missing, the corresponding section measuring point is removed (i.e., the complete record line for removing the section measuring point is removed). The line number of the removed section measuring point and the name of the missing field are recorded, and a prompt message indicating a change in the number of measuring points for the river section is generated (i.e., the number of measuring points is reduced from the original number to the number of measuring points after removal).

[0037] Preferably, data type checking and processing includes: performing floating-point parsing on the starting distance and elevation fields using a forced type conversion method; if parsing fails, it is determined to be a type anomaly. Cross-section measuring points determined to be type anomalies are directly removed, the reason for the anomaly and the corresponding row number are recorded, and a data type anomaly log is generated. If the number of measuring points with type anomalies in a certain river cross-section data exceeds 30% of the total number of cross-section measuring points in that river cross-section data, the subsequent processing flow for that river cross-section is suspended, and it is transferred to the manual review queue.

[0038] Preferably, error character checking and processing includes: The regular expression whitelist filtering method is used to define a legal character set (including numbers, decimal points, plus and minus signs, etc.) and perform a full file scan on the river cross-section data (including metadata area and data table area) to match and identify all illegal characters that do not belong to the legal character set.

[0039] For detected illegal characters, they are directly removed from the original field, retaining valid character content; full-width numbers and letters are automatically mapped to half-width characters and included in the legal character set. The type and quantity of characters cleaned in each field are recorded, generating a data cleanup record. If a cell is empty after cleanup, it is marked as a missing value and transferred to data missing value checking and processing.

[0040] Preferably, the checking and handling of outliers in elevation data includes: A statistical threshold-based method is used to determine elevation anomalies. A measuring point is considered an elevation anomaly if it meets the following conditions: in, Indicates the first Elevation of each cross-section measuring point Indicates the first The median elevation of all measuring points along the river section where the measuring point is located. Indicates the first The absolute median difference in elevation of all measuring points on the river section where the measuring point is located.

[0041] For cross-sectional measuring points identified as elevation anomalies, their elevations are corrected using linear interpolation. The correction formula is as follows: in, Indicates the first The corrected elevation of each cross-section measuring point Indicates the first Elevation of each cross-section measuring point Indicates the first Elevation of each cross-section measuring point.

[0042] Preferably, the target data fields extracted from the river cross-section data according to the data requirements of the MIKE model include: river name, river cross-section number, cross-section mileage location, coordinates of the left endpoint of the cross-section, coordinates of the right endpoint of the cross-section, distance between the starting point and the measuring point of the cross-section, elevation of the measuring point of the cross-section, and description of the geomorphic features of the measuring point of the cross-section.

[0043] Furthermore, all extracted target data fields are strictly standardized according to the data format specifications of the MIKE model. The standardization process in this embodiment includes data type conversion, unit unification, and precision control. The rules for standardizing the target data fields in this embodiment are shown in Table 3. Table 3 Standardization rules for target data fields In Table 3, This represents the X-coordinate value of the left endpoint of the cross-section in the coordinate system of the river channel cross-section. This represents the Y-coordinate value of the left endpoint of the cross-section in the coordinate system of the river channel cross-section. This represents the X-coordinate value of the right endpoint of the cross-section in the coordinate system of the river channel cross-section. This represents the Y-coordinate value of the right endpoint of the cross-section in the coordinate system of the river channel cross-section; This indicates the distance from the starting point of the measuring point on the cross section, that is, the horizontal distance from the starting point of the cross section along the cross section direction of the river channel; This represents the elevation values ​​of the cross-section measuring points. After standardization, the fields are organized according to the data format specifications of the MIKE model to form set B.

[0044] In this context, the user marker corresponds to the User marker field (i.e., user-defined marker) in the MIKE model cross-section file. In the MIKE model, markers 1 to 7 are system-predefined markers (corresponding to the left bank, lowest point, right bank, etc.), with specific calculation functions; while markers greater than 7 are user-defined markers, which do not affect the model calculation results and are only used to identify specific points on the cross-section (such as monitoring station locations). The value of the user marker is defined by the user according to their actual needs.

[0045] Preferably, the data of river cross-sections belonging to the same river cross-section in set B are merged, specifically: When there are two or more river cross-section data in set B with completely identical river names and river cross-section numbers, it is determined that these river cross-section data belong to the same wide cross-section and are classified into the same candidate group. The data of each river section within the same candidate group are sorted in ascending order of distance from the starting point to determine the left-right positional relationship of each river section data on the actual riverbed. After sorting, two adjacent river section data are subjected to a dual-condition judgment of spatial continuity and elevation consistency. If the dual-condition judgment is satisfied, the two adjacent river section data are merged into the same section data in a head-to-tail manner. The merged section data and the next adjacent river section data continue to be subject to dual-condition judgment and merging processing, and so on, until all river section data in the candidate group are processed. If the data of two adjacent river sections do not meet either the spatial continuity or elevation consistency criteria, the merging process will be terminated, and a corresponding alarm will be triggered based on the type of criterion that is not met.

[0046] Furthermore, the dual-condition determination of spatial continuity and elevation consistency specifically includes: 1) Determination of spatial continuity: In the sorted data of two adjacent river cross sections, the river cross section data in the earlier order is denoted as segment A, and the river cross section data in the later order is denoted as segment B. The end point of segment A is the measuring point with the largest starting point distance in the segment, and the beginning point of segment B is the measuring point with the smallest starting point distance in the segment.

[0047] Calculate the spatial distance between the end point of segment A and the beginning point of segment B. , which is the absolute value of the difference between the starting distance of the end point of segment A and the starting distance of the beginning point of segment B.

[0048] like Determine that segment A and segment B are spatially continuous; like Segment A and segment B are determined to be quasi-continuous. Quasi-continuous means that there is a small gap between the two segments. This gap can be supplemented by interpolation and does not affect merging. like Segment A and segment B are determined to be spatially discontinuous and cannot be merged.

[0049] in, Take 0.5 times the smaller average measurement point spacing between segments A and B. Take 2-3 times the smaller average measurement point spacing between segments A and B. If the river width is extremely large (such as the Yangtze River), determine the threshold. and It can be enlarged appropriately according to the scale.

[0050] 2) Determination of Elevation Consistency: when When calculating the elevation difference between the end point of segment A and the beginning point of segment B, directly calculate the absolute value of the difference. .

[0051] when At that time, linear extrapolation is performed based on the two measuring points at the end of segment A and the two measuring points at the beginning of segment B to obtain the extrapolated elevation values. Then, the absolute value of the difference between the two extrapolated elevation values ​​is calculated. .

[0052] like The elevations were determined to be consistent. like The elevations are inconsistent and cannot be merged.

[0053] Among them, the judgment threshold Take the smaller of 5% of the maximum elevation difference of the measuring points in the candidate group and the fixed value of 0.5m.

[0054] Furthermore, when This means that there is a small gap between two adjacent segments A and B (i.e., the endpoint of segment A and the starting point of segment B are not continuous in terms of the distance between their starting points, and there is a gap). To determine whether the elevation transition between the two segments at the gap is smooth, it is necessary to extrapolate and estimate the elevation values ​​at both ends of the gap based on the topographic trends of segments A and B respectively, and then compare them, as follows: Assume the starting distances of the two measuring points at the end of segment A are respectively and (in The distance from the starting point of the end point of segment A. (The distance from the starting point of the second-to-last measuring point in segment A), and the corresponding elevations are respectively and Local slope at the end point of segment A It can be calculated using the following formula: Based on local slope Extrapolate the topographic trend of segment A to the starting point of segment B, and estimate the extrapolated elevation value at the starting point of segment B. : in, The distance between the starting points of segment B and the beginning of segment B.

[0055] Similarly, assuming the starting distances of the two measuring points at the beginning of segment B are respectively... and (in The distance between the starting points of segment B and the starting point of segment B. (The distance from the starting point of the second measuring point in segment B), the corresponding elevations are respectively and Local slope at the beginning and end of segment B Calculate using the following formula: Based on local slope Extrapolate the topographic trend of segment B to the end point of segment A, and estimate the extrapolated elevation value at the end point of segment A. : Obtain extrapolated elevation values and Next, calculate the absolute value of their difference: like A smaller value indicates that the terrain change trends of the two segments at the gap can be naturally connected, satisfying the elevation consistency requirement; if... If the gap is too large, it indicates that there are obvious steps or jumps in the terrain on both sides of the gap, which does not meet the requirement of consistent elevation.

[0056] 3) Comprehensive judgment: When the space is continuous and the elevation is consistent, it is determined that both conditions are met, and segment A and segment B can be merged. When spatial continuity is not consistent with elevation, an alarm for suspected geological change or measurement system error is triggered, merging is terminated, and manual review is initiated. When the spatial structure is discontinuous but the elevation is consistent, an alarm is triggered indicating that the numbers are duplicated but the locations are different. Merging is refused, and segment A and segment B are marked as independent sections for storage. When the space is discontinuous and the elevation is inconsistent, the merging is terminated, and segment A and segment B are marked as independent sections for storage.

[0057] Preferably, to uniformly convert river cross-section data under different elevation datums into the elevation datum used for MIKE model calculations, this embodiment incorporates an elevation datum conversion parameter library within the system to store conversion parameters between different elevation datums. When the elevation datum labeled on the river cross-section data in set C is inconsistent with the target elevation datum used for MIKE model calculations, the corresponding conversion parameter is retrieved from the conversion parameter library, and the elevation values ​​of all cross-section measuring points are uniformly converted. After the conversion is completed, the river cross-section data with the unified elevation datum is stored in set D. If the corresponding conversion relationship does not exist in the conversion parameter library, the conversion is performed according to the conversion parameters input by the user.

[0058] Furthermore, the elevation datum transformation adopts the fixed constant translation method, and the transformation function is expressed as: in, This represents the converted elevation value. This represents the original elevation value. This represents the fixed elevation difference between the original elevation datum and the target elevation datum.

[0059] Preferably, based on the storage order of the cross-section measuring points in set D and the elevation data, the characteristic points of the river channel cross-section are identified, including the thalweg point, the left bank levee point, the right bank levee point, the left bank beach-channel boundary point, and the right bank beach-channel boundary point.

[0060] The method for identifying the thalweg point is as follows: the position corresponding to the minimum elevation among all cross-sectional measuring points of the same river section is taken as the thalweg point; the method for identifying the left bank levee point is as follows: in the same river section, taking the thalweg point as the boundary, the position corresponding to the maximum elevation among all cross-sectional measuring points stored before the thalweg point is taken as the left bank levee point; the method for identifying the right bank levee point is as follows: in the same river section, taking the thalweg point as the boundary, the position corresponding to the maximum elevation among all cross-sectional measuring points stored after the thalweg point is taken as the right bank levee point.

[0061] Furthermore, the method for identifying the boundary points between the left bank floodplain and the right bank floodplain is as follows: First, the Savitzky-Golay filter (local polynomial fitting smoothing) is used to smooth the elevation sequence of the river cross-section to eliminate noise in the measurement data. The smoothing formula is as follows: in, Indicates the first Elevation of each cross-section measuring point Indicates the first Elevation of each cross-section measuring point after smoothing Indicates the window radius. This represents the convolution coefficients of the least-squares fitting polynomial. Specifically, the window radius... Based on the density of measuring points along the cross-section, taking the data from the 10 measuring points shown in Table 1 as an example, there are no measurement error jumps in this river cross-section data, therefore no special smoothing is required. The value can be 1.

[0062] Then, calculate the slope sequence (first derivative) of each measuring point on the smoothed river cross-section, using the following formula: in, Indicates the first The slope of each cross-section measuring point Indicates the first The distance from the starting point of each cross-section measuring point Indicates the first Elevation of each cross-section measuring point after smoothing Indicates the first The distance from the starting point of each cross-section measuring point Indicates the first Elevation of each cross-section measuring point after smoothing; Further calculation of the curvature sequence (second derivative) at each measuring point of the river channel cross-section is given by the following formula: in, Indicates the first Curvature of each cross-sectional measuring point Indicates the first The slope of each cross-section measuring point Indicates the first The slope of each cross-section measuring point.

[0063] Calculate the absolute value of the slope difference at each measuring point on the river cross-section: The river channel cross section is divided using the thalweg point, the left bank levee point, and the right bank levee point as the interval boundaries, resulting in the interval from the left bank levee point to the thalweg point and the interval from the thalweg point to the right bank levee point. Within the interval from the left bank levee point to the thalweg point, select the curvature Furthermore, the location with the largest absolute value of the slope difference is taken as the boundary point between the left bank floodplain and the river channel. This represents the curvature of any cross-sectional measuring point within the interval from the left bank levee point to the thalweg point; Within the interval from the thalweg point to the right bank levee point, select the curvature Furthermore, the location with the largest absolute value of the slope difference is taken as the boundary point between the right bank floodplain and the river channel. It represents the curvature of any cross-sectional measuring point within the interval from the thalweg point to the right bank levee point.

[0064] After identification, each feature point is marked and its location and elevation information is stored. The identified feature points can be directly used for boundary condition setting and result visualization of the MIKE model, providing feature parameters for subsequent model calculation and cross-sectional morphology analysis.

[0065] Furthermore, to enable those skilled in the art to better understand how to identify feature points of a river cross-section, this embodiment uses the data from 10 cross-sectional measurement points shown in Table 1 to illustrate feature point identification: Table 4 Feature Points of River Cross-Section Data As shown in Table 4 and Figure 2As shown, the elevation data of the measuring point corresponding to section number 6 is 1 meter, which is the minimum elevation and should be identified as a thalweg point. Based on this, the left bank levee point is the highest elevation among the section measuring points stored in the order of relative thalweg point location. Among them, the elevation data of the measuring point corresponding to section number 2 is 8 meters, which is the highest elevation before the thalweg point at section number 6, and should be identified as a left bank levee point. The right bank levee point is the highest elevation among the section measuring points stored in the order of relative thalweg point location. Among them, the measuring point corresponding to section number 9... The elevation data is 9 meters, which is the highest elevation after the thalweg point number 6, and should be identified as the right bank levee point; within the interval from number 2 to number 6 to the left of the thalweg point, the curvature at point 4 is less than 0, and the absolute value of the difference in slope before and after is the largest, so the measuring point at the section corresponding to point 4 is identified as the boundary point between the left bank beach and the river channel; within the interval from number 6 to number 9 to the right of the thalweg point, the curvature at point 7 is less than 0, and the absolute value of the difference in slope before and after is the largest, so the measuring point at the section corresponding to point 7 is identified as the boundary point between the right bank beach and the river channel.

[0066] Preferably, the roughness value of each cross-section measuring point is determined based on the geomorphic feature description of the cross-section measuring points in set D, and the roughness parameter of the river channel cross-section is calculated, specifically: Based on the geomorphic feature descriptions of each cross-section measuring point, the roughness value of each cross-section measuring point is determined by referring to a pre-set roughness value table. The geomorphic feature descriptions include underwater features, grass, shrubs, asphalt roads, ditches, paddy fields, and field ridges. The roughness value table is established based on recommended roughness values ​​in the field of water conservancy engineering, assigning corresponding roughness values ​​to different geomorphic feature types.

[0067] The roughness parameter of the river channel cross section is the overall roughness of the river channel cross section. The roughness values ​​of each cross section measuring point are weighted and averaged to obtain the overall roughness of the river channel cross section.

[0068] Suppose a certain river cross section is composed of Composed of ... The roughness of each cross-section measuring point is The representative width corresponding to the measuring point of this section is The overall roughness of the river channel cross section is then... Calculate using the following formula: in, The overall roughness of the river channel cross section is dimensionless. For the first Roughness at each cross-sectional measuring point, dimensionless; For the first The representative width of each cross-sectional measuring point, in meters, is determined by the distance between the starting points of adjacent cross-sectional measuring points using the virtual boundary method, i.e., defining virtual boundary points. and ,in , ,Right now , For the first The distance between the starting points of each cross-section measuring point; This represents the total number of measuring points on the cross-section.

[0069] To enable those skilled in the art to better understand how to calculate the overall roughness of a river channel cross-section, this embodiment uses data from 10 cross-sectional measurement points as shown in Table 1 to further illustrate how to determine the roughness value and the overall roughness of the river channel cross-section. The calculation results, rounded to the nearest whole number, are shown in Table 5. Table 5 Calculation Table for River Channel Cross-Section Roughness Values Based on the notes in Table 1, and according to the geomorphological characteristics of conventional cross-section points such as underwater, grass, shrubs, asphalt roads, ditches, paddy fields, and field ridges, and referring to the recommended roughness values ​​for different riverbeds in Tables 2-2-8 to 2-2-10 and Tables 8-1-4 to 8-1-6 of the "Hydraulic Calculation Handbook" (Li Wei, pp. 45, 363-366, China Water Resources and Hydropower Press, 2006), the roughness values ​​of each cross-section measuring point are determined. The comprehensive roughness of the river cross-section is determined by weighting and summing the roughness values ​​of all cross-section measuring points according to the representative width of the cross-section measuring points.

[0070] For example, the remarks column corresponding to section 1 in Table 1 indicates asphalt road. Referring to the "Hydraulic Calculation Handbook" (Li Wei, page 45, China Water Resources and Hydropower Press, 2006), the recommended roughness value for asphalt concrete-machined on-site casting with a rough surface in Table 2-2-10 (Ruttyness Value Table for Anti-seepage Lined Channels) is 0.015-0.017. Based on industry experience, the average of the upper and lower limits is generally taken as (0.015+0.017) / 2=0.016. After calculating the roughness for all 10 section measuring points, the comprehensive roughness of the entire river channel section needs to be calculated using the representative width of each section measuring point as a weight. This comprehensive roughness serves as an important parameter in the MIKE model calculation.

[0071] Specifically, For the first The representative width of each cross-sectional measuring point is the effective projected width of the measuring point in the horizontal direction. It is calculated using the virtual boundary method, which defines virtual boundaries in front of the first endpoint and behind the last endpoint of the river cross-section, so that the first and last measuring points and the virtual boundaries constitute a complete control area. In this embodiment, the total length of the cross-section is 11.5-0=11.5m. Taking number 1 as an example, its representative width is (1-0) / 2 = 0.5m, and its weight is 0.5 / 11.5≈0.043; taking number 2 as an example, its representative width is (2.1-0) / 2 = 1.05m, and its weight is 1.05 / 11.5≈0.091; taking number 3 as an example, its representative width is (4.1-1) / 2 = 1.55m, and its weight is 1.55 / 11.5≈0.135; taking number 10 as an example, its representative width is (11.5-11) / 2 = 0.25m, and its weight is 0.25 / 11.5≈0.022; and so on, calculating the weights of other numbered data points. The sum of the representative widths of all cross-sectional measurement points equals the total cross-sectional width of 11.5m.

[0072] Finally, the river cross-section data in set D, along with the feature point information of each cross-section identified in step S7 (including the location and elevation of the thalweg point, left bank levee point, right bank levee point, left bank floodplain-channel boundary point, and right bank floodplain-channel boundary point), and the comprehensive roughness parameters of each cross-section calculated in step S8, are finally processed according to the standard cross-section data format of the MIKE model. The processed cross-section data is output in a cross-section file format that can be directly called by the MIKE model for use in MIKE model hydrodynamic modeling and simulation calculations.

[0073] This embodiment integrates the entire process of converting multi-source heterogeneous river cross-section data into the MIKE model standard format into an automated processing flow. The system automatically identifies the data format through seven-dimensional feature vector template matching, eliminating the need for users to pre-specify or write parsing scripts. It automatically performs four types of checks and processing: missing data, data type, erroneous characters, and elevation outliers, preventing the entire cross-section from being invalidated due to problems with individual measuring points. For wide cross-sections, it automatically identifies and merges segmented data through dual-condition judgment, ensuring the integrity and continuity of the cross-section morphology. Feature point identification directly uses the storage order of cross-section measuring points and elevation data to determine the thalweg point, levee point, and channel-shoal boundary point. Roughness calculation is automatically completed based on geomorphological feature descriptions. These steps constitute a complete pathway from raw data to MIKE model cross-section files, significantly reducing manual processing workload and data error rates.

[0074] Example 2: This embodiment provides another method for converting multi-source heterogeneous river cross-section data into a MIKE model. The difference between this embodiment and Embodiment 1 lies in the calculation method of the roughness parameter of the river cross-section in step S8. This embodiment achieves an upgrade from the overall comprehensive roughness of the river cross-section to the refined partitioned roughness by refining the roughness partitions, and calculating the comprehensive roughness of each partition by weighting it according to the representative width. This provides more accurate riverbed resistance parameters for the MIKE model.

[0075] In this embodiment, the roughness value of each cross-section measuring point is determined based on the geomorphic feature description of the cross-section measuring points in set D, and the roughness parameter of the river channel cross-section is calculated, specifically: S8.1. Based on the geomorphic feature description of each cross-section measuring point, determine the roughness value of each cross-section measuring point by referring to the preset roughness value table. S8.2 Using the identified thalassic point, the boundary between the left bank beach and the right bank beach, the river channel cross section is divided into multiple roughness zones, wherein the roughness zones include at least the main channel area and the beach area. S8.3. Using the representative width of each cross-sectional measuring point within the roughness zone as the weight, the roughness values ​​of each cross-sectional measuring point within the roughness zone are weighted and averaged to obtain the comprehensive roughness of the roughness zone. S8.4. Perform physical rationality and spatial consistency checks on the comprehensive roughness of each roughness zone of the river section; if any roughness zone of a certain river section fails any check, the processing of that river section shall be stopped and the river section shall be marked as pending manual review.

[0076] Preferably, in this embodiment, the roughness value of each cross-section measuring point is determined by referring to a preset roughness value table based on the geomorphic feature description of each cross-section measuring point. The geomorphic feature description includes underwater features, grass, shrubs, asphalt roads, ditches, paddy fields, and field ridges. The roughness value table is established based on recommended roughness values ​​in the field of water conservancy engineering, assigning corresponding roughness values ​​to different geomorphic feature types. In this embodiment, the method for determining the roughness of a single point is the same as in Embodiment 1, and will not be repeated here.

[0077] Preferably, using the thalweg point, the left bank floodplain-channel boundary point, and the right bank floodplain-channel boundary point identified in step S7, the river channel cross-section is divided into multiple roughness zones, specifically: The river channel is divided into three primary regions based on the boundary between the left bank floodplain and the right bank floodplain: the left floodplain region (from the left end of the cross-section to the boundary between the left bank floodplain and the right bank floodplain), the main channel region (from the boundary between the left bank floodplain and the right bank floodplain), and the right floodplain region (from the boundary between the right bank floodplain and the right bank floodplain).

[0078] After obtaining the three primary regions, each of the three primary regions is further subdivided into secondary regions: 1) Refined internal zoning of the main tank area: Using the thalweg point as a reference, the curvature (second derivative) of each cross-sectional measuring point in the main channel area is calculated point by point, and the position with the largest absolute value of curvature is selected as the internal boundary inflection point. Within the main channel area to the left of the thalweg point (i.e., within the interval from the boundary between the left bank floodplain and the channel to the thalweg point), the location with the largest absolute value of curvature is selected as the dividing point between the left main channel slope area and the main channel thalweg area. ; Within the main channel area to the right of the thalweg point (i.e., the interval between the thalweg point and the boundary point between the right bank floodplain and the main channel), the location with the largest absolute value of curvature is selected as the dividing inflection point between the right main channel slope area and the main channel thalweg area. ; Through the dividing inflection point and The main channel area is divided into the left main channel slope area (from the left bank beach river channel boundary to the left boundary inflection point). ), main channel deepwater zone (left boundary inflection point) To the right dividing point ) and the right main channel slope area (right boundary inflection point) (to the boundary between the right bank beach and the river channel). Specifically, the curvature (second derivative) of each cross-sectional measuring point within the main trench area is calculated in the same way as in the embodiment, therefore, it will not be described in detail in this embodiment.

[0079] 2) Refined internal zoning of the left and right beach areas: Starting from the boundary point between the riverbed and the beach area identified in step S7, calculate the elevation change point by point in the direction away from the main channel area. If the single-step elevation rise between two or more consecutive adjacent cross-sectional measuring points from a certain cross-sectional measuring point exceeds the preset threshold, the change will be considered as a result of the previous calculation. If the elevation rise from the measuring point on that section continuously exceeds the preset threshold, then... The cross-sectional measuring points are recorded as sequence P. The first cross-sectional measuring point in sequence P (i.e., the starting position closest to the boundary between the riverbed and the floodplain, and where the elevation first shows a continuous upward trend) is determined as a candidate boundary point. The candidate boundary point is then cross-validated based on the geomorphic features described by the cross-sectional measuring points. The preset threshold... It can be determined based on a certain proportion of the total elevation difference of the river channel cross section (such as taking 10% of the total elevation difference of the river channel cross section) to reflect the abrupt topographic changes in the transition of the beach area from the near channel area to the high beach area.

[0080] The specific method of cross-validation is as follows: obtain the geomorphic feature description of the candidate boundary point and its adjacent cross-sectional measuring points. If the geomorphic feature at the candidate boundary point changes type compared to the geomorphic feature of the adjacent measuring points on the side closer to the main channel (e.g., from "grass" to "shrubs" or "asphalt road"), then the cross-validation is passed, and the candidate boundary point is finally determined as the boundary point between the near-channel beach and the far-channel high beach. If the geomorphic features at the candidate boundary point do not change in type, cross-validation fails. In this case, the system records the anomaly and generates a prompt, marking the candidate boundary point as requiring manual review, or selecting the next cross-sectional measuring point in sequence P as a new candidate boundary point for re-cross-validation, until cross-validation passes or sequence P is traversed completely. If cross-validation still fails after sequence P is traversed completely, the initial candidate boundary point is designated as the beach boundary point, and a corresponding prompt is generated for manual confirmation. It should be noted that the geomorphic feature description is obtained as follows: the geomorphic feature description of each cross-sectional measuring point is already saved in set B after standardization processing in step S4 of Example 1, along with the cross-sectional measuring point data. Therefore, during boundary point verification, the geomorphic feature description field of the corresponding measuring point can be directly read from set B.

[0081] Specifically, within the left bank floodplain area, starting from the boundary point between the left bank floodplain and the river channel, the elevation change between adjacent cross-sectional measuring points is calculated point by point to the left. When the elevation rise of two or more consecutive measuring points exceeds a preset threshold, the change is considered complete. When this group continuously exceeds the preset threshold, The location of the first cross-sectional measuring point (i.e., the starting point where the elevation begins to rise significantly and is closest to the boundary between the river channel and the left near-channel riverbank) is determined as the boundary between the left far-channel high riverbank and the left near-channel high riverbank. Simultaneously, referring to the geomorphological descriptions of the cross-sectional measuring points near this boundary, if the geomorphological features change from "grass" to "shrubs" or "asphalt road," the rationality of the boundary point is further verified. The same principle applies to the right riverbank area.

[0082] Therefore, the Zuotan area is further subdivided into: Left bank floodplain area: from the boundary between the river channel and the left bank floodplain to the boundary between the floodplain and the inner floodplain on the left side; Left Yuan Channel High Beach Area: From the boundary point of the beach inside the left side beach to the left end point of the cross section.

[0083] The Youtan area is further subdivided into: Right bank near channel area: from the boundary point of the right bank channel to the boundary point of the inner channel of the right bank; Right-hand high shoal area: from the boundary point of the shoal within the right-hand shoal to the right end point of the cross section.

[0084] In summary, this embodiment divides the river channel cross-section into up to seven refined roughness zones: the left distal channel high shoal zone, the left near channel shoal zone, the left main channel slope zone, the main channel thoroughfare zone, the right main channel slope zone, the right near channel shoal zone, and the right distal channel high shoal zone. Specifically, when the boundary inflection point between the main channel slope zone and the main channel thoroughfare zone on a certain side coincides with the boundary point between the shoal and the channel, the main channel slope zone on that side is not considered an independent zone, and the number of corresponding zones is reduced.

[0085] The boundary locations of each roughness zone are determined by the thalweg point, the boundary point between the floodplain and the channel identified in step S7, and the inflection points of the internal zones automatically identified based on the curvature and elevation change trends. Each channel cross-section outputs a structured roughness zone table, which includes: zone number, zone name, starting point distance range, measurement point number within the zone, representative width of the zone, and zone roughness value.

[0086] Preferably, the overall roughness of each roughness zone is calculated by weighting the roughness values ​​of the cross-sectional measuring points contained within that zone according to the representative width: in, Indicates the first The overall roughness of each roughness zone. Indicates the first The total number of cross-sectional measuring points in each roughness zone For the first Roughness of each cross-sectional measuring point For the first The representative width of each cross-sectional measuring point is also determined by the distance between the starting points of adjacent cross-sectional measuring points using the virtual boundary method.

[0087] Preferably, a physical rationality check is performed on the overall roughness of the roughness zone, specifically: If the overall roughness of a roughness zone exceeds its corresponding reasonable preset range, or if the relative relationship between the overall roughness of each roughness zone violates the preset physical laws (i.e., the overall roughness of the beach is less than the overall roughness of the main channel), then the physical rationality check of the river section fails. In this case, the subsequent processing of the river section is terminated, and the river section is marked for manual review. The reason for failure is recorded in the quality report (specifically, which roughness zone exceeds the range, or which two roughness zones have an abnormal relative relationship). The manual reviewer determines whether the roughness value needs to be adjusted or the description of the geomorphological features needs to be reconfirmed based on the actual geomorphological features. If the actual geomorphological features do indeed cause the roughness of the beach to be less than the roughness of the main channel (e.g., the beach is smooth bedrock), the section can be released after manual confirmation.

[0088] Specifically, in this embodiment, the preset physical laws between the seven refined roughness zones are expressed as follows: comprehensive roughness of the high beach area of ​​the far channel ≥ comprehensive roughness of the beach area of ​​the near channel ≥ comprehensive roughness of the slope area of ​​the main channel ≥ comprehensive roughness of the deep water area of ​​the main channel.

[0089] Preferably, a spatial consistency check is performed on the overall roughness of each roughness partition, specifically: For all cross-sections of the same river channel, roughness zones of the same type are sorted according to their cross-section mileage, forming a sequence of comprehensive roughness variation along the river's course for each roughness zone. The relative rate of change of comprehensive roughness for the same type of roughness zones in adjacent cross-sections is calculated on a per-cross-section basis, using the following formula: in, Indicates the first The first of the river cross sections The overall roughness of roughness partitions, Indicates the first The first of the river cross sections The overall roughness of roughness partitions.

[0090] If the relative rate of change of the overall roughness of the same type of roughness zone in two adjacent river cross sections exceeds a preset threshold (the preset threshold is 50% in this embodiment), the system automatically marks the adjacent river cross section combination (i.e., the first...). The river cross section and the first If a river section fails the spatial consistency check, the system will generate a prompt message, recording the river section number, roughness zone name, comprehensive roughness, and relative change rate of comprehensive roughness. It is recommended that the data be manually verified. The manual verification should be based on the actual changes in river geomorphology to determine whether the change is reasonable (such as abrupt changes in riverbed geology) or whether there are any data errors.

[0091] Once both checks are completed, the system summarizes all warning messages and corresponding cross-sectional locations, generating a cross-sectional roughness partition quality report for user review and confirmation.

[0092] Preferably, the river cross-section data in set D, along with the cross-section feature point information identified in step S7 (including the location and elevation of the thalweg point, left bank levee point, right bank levee point, left bank floodplain-channel boundary point, and right bank floodplain-channel boundary point), the zoning information of each roughness zone calculated in step S8 (including zone number, zone name, starting point distance range, and zone roughness value), and the cross-section roughness zone quality report generated in step S8.4, are finally processed according to the standard cross-section data format of the MIKE model. The roughness zone information is written to the cross-section file in the Roughness zone format supported by the MIKE model.

[0093] The processed cross-sectional data is output in a cross-sectional file format that can be directly called by the MIKE model. At the same time, the cross-sectional roughness partition quality report is also output as an auxiliary file for use in MIKE model hydrodynamic modeling and simulation calculation.

[0094] This embodiment, based on Embodiment 1, upgrades the roughness parameter from a single overall comprehensive roughness to a refined zonal roughness. The system uses the thalweg point and the boundary between the shoal and the channel to divide the river cross-section into multiple zones, such as the main channel thalweg zone, the main channel slope zone, and the shoal zone. Each zone independently calculates its comprehensive roughness and outputs a zoning table, which more accurately reflects the actual resistance characteristics of each area compared to the overall roughness. Simultaneously, the system sequentially performs physical rationality checks and spatial consistency checks on the zoning results. Both checks are mandatory; if either check fails, the processing of that cross-section is terminated and marked for manual review. The quality report records the reasons for failure in detail, avoiding the direct input of unreasonable or contradictory roughness parameters into the MIKE model calculation.

[0095] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for converting multi-source heterogeneous river cross-section data into a MIKE model, characterized in that, include: Obtain a set A consisting of multi-source heterogeneous river cross-section data; The structural features of the river cross-section data in set A are compared with the structural features of the preset data template to determine the format type of the river cross-section data; Based on the data template corresponding to the river cross-section data, anomaly checks and processing are performed on the river cross-section data; According to the data requirements of the MIKE model, target data fields are extracted from the river cross-section data, and set B is obtained after standardizing the target data fields; The data of river cross sections belonging to the same river cross section in set B are merged to obtain set C; The river cross-section data in set C are converted into the elevation datum used in the MIKE model calculation to obtain set D; Based on the storage order of the cross-section measurement points and elevation data in set D, identify the characteristic points of the river channel cross-section; Based on the geomorphic feature description of the cross-section measuring points in set D, determine the roughness value of each cross-section measuring point, and calculate the roughness parameter of the river channel cross-section; The river cross-section data in set D, along with the corresponding feature points and roughness parameters, are organized into the cross-section data format required by the MIKE model.

2. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 1, characterized in that, Determine the format type of the river cross-section data, specifically: Extract the structural feature vectors of the river cross-section data and each data template; Adopting the first The structural feature vector of the first river cross-section data and the first Weighted Euclidean distance between the structural feature vectors of each data template To measure the similarity between the two; The calculated weighted Euclidean distances are sorted in ascending order. ,calculate and The relative distance between ; like Then the first The data of each river cross section were directly matched using a weighted Euclidean distance. The format type of the corresponding data template; if Then the first The data from individual river cross-sections were initially matched using weighted Euclidean distance. The format type of the corresponding data template is displayed, and a manual review is prompted; if Then it is considered that the first No matching data template was found for the river cross-section data; in, This indicates the total number of preset data templates. , This represents the data of any river cross-section in set A.

3. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 1, characterized in that, Anomaly checks and processing were performed on the river cross-section data, specifically: Data missing detection and handling: For each cross-section measurement point record, check for empty or missing values ​​in the fields of river name, river cross-section number, cross-section mileage location, starting distance, and elevation. If the river name, river cross-section number, or cross-section mileage location field is missing, the processing flow for that river cross-section is suspended and marked as awaiting manual entry. If the starting distance or elevation field is missing, the corresponding cross-section measurement point is removed and recorded. Data type checking and processing: The starting distance and elevation fields are parsed as floating-point numbers using a forced type conversion method. If the parsing fails, it is judged as a type anomaly and the corresponding cross-section measurement points are removed. If the number of cross-section measurement points with type anomalies in a certain river cross-section data exceeds the preset proportion of the total number of cross-section measurement points in the river cross-section data, the subsequent processing of the river cross-section is suspended and transferred to manual review. Error character detection and handling: Illegal characters are identified and cleaned up using regular expression whitelist filtering. Full-width numbers and letters are automatically mapped to half-width characters. If a cell is empty after cleaning, it is marked as a missing value and transferred to data missing detection and handling. Elevation data outlier detection and handling: An elevation outlier is determined using a statistical threshold-based method. When the elevation value of a cross-section measuring point is outside the range of absolute median difference that is a preset multiple of the median of all measuring points in the river cross-section, the measuring point is determined to be an elevation outlier. For the cross-section measuring points determined to be elevation outliers, their elevation is corrected using linear interpolation.

4. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 1, characterized in that, The data of river cross sections belonging to the same river cross section in set B are merged, specifically: When there are two or more river cross-section data in set B with completely identical river names and river cross-section numbers, it is determined that these river cross-section data belong to the same wide cross-section and are classified into the same candidate group. The data of each river section within the same candidate group are sorted in ascending order of distance from the starting point to determine the left-right positional relationship of each river section data on the actual riverbed. After sorting, two adjacent river section data are subjected to a dual-condition judgment of spatial continuity and elevation consistency. If the dual-condition judgment is satisfied, the two adjacent river section data are merged into the same section data in a head-to-tail manner. The merged section data and the next adjacent river section data continue to be subjected to dual-condition judgment and merging processing, and so on, until all river section data in the candidate group are processed. If the spatial continuity or elevation consistency conditions of two adjacent river section data are not met, the merging process will be terminated, and an alarm will be triggered according to the type of condition that is not met.

5. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 4, characterized in that, For two adjacent river cross-sections after sorting, a dual-condition judgment is made on spatial continuity and elevation consistency. Specifically: Spatial continuity determination: In the sorted two adjacent river cross-section data, the river cross-section data in the earlier order is denoted as segment A, and the river cross-section data in the later order is denoted as segment B. The end point of segment A is the cross-section measuring point with the largest starting point distance in the segment, and the beginning point of segment B is the cross-section measuring point with the smallest starting point distance in the segment. Calculate the spatial distance between the end point of segment A and the beginning point of segment B. ;like If it is determined to be spatially continuous; If it is determined to be quasi-continuous; This is determined to be a spatial discontinuity; Elevation consistency determination: When When calculating the elevation difference between the end point of segment A and the beginning point of segment B, directly calculate the absolute value of the difference. ;when At that time, linear extrapolation was performed based on the measuring points at the last two sections of segment A and the first two sections of segment B to obtain extrapolated elevation values. The absolute value of the difference between the two extrapolated elevation values ​​was then calculated. ;like If the elevation is consistent, it is determined that the elevation is consistent; This was determined to be due to inconsistent elevations; Comprehensive judgment: When the spatial continuity judgment result is spatial continuity or quasi-continuity, and the elevation consistency judgment result is elevation consistency, then the dual condition judgment is satisfied; Otherwise, the two conditions are not met; in, , and All of these are judgment thresholds.

6. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 1, characterized in that, The key points for identifying a river channel cross-section include the thalweg point, the left bank levee point, the right bank levee point, the boundary between the left bank beach and the river channel, and the boundary between the right bank beach and the river channel.

7. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 1, characterized in that, Based on the geomorphic feature description of the cross-section measuring points in set D, the roughness values ​​of each cross-section measuring point are determined, and the roughness parameters of the river channel cross-section are calculated, specifically: Based on the geomorphic features of each cross-section measuring point, the roughness value of each cross-section measuring point is determined by referring to the preset roughness value table. The roughness parameter of the river channel cross-section is the overall roughness of the river channel cross-section. The roughness values ​​of each cross-section measuring point are weighted and averaged to obtain the overall roughness of the river channel cross-section.

8. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 6, characterized in that, Based on the geomorphic feature description of the cross-section measuring points in set D, the roughness values ​​of each cross-section measuring point are determined, and the roughness parameters of the river channel cross-section are calculated, specifically: Based on the geomorphic features of each cross-section measuring point, the roughness value of each cross-section measuring point is determined by referring to the preset roughness value table. Using the identified thalassium point, the boundary between the left bank beach and the right bank beach, the river cross section is divided into multiple roughness zones. Using the representative width of each cross-sectional measuring point within the roughness zone as the weight, the roughness values ​​of each cross-sectional measuring point within the roughness zone are weighted and averaged to obtain the comprehensive roughness of the roughness zone. The physical rationality and spatial consistency of the comprehensive roughness of each roughness zone of the river section are checked. If any roughness zone of a river section fails any check, the processing of that river section is stopped and the river section is marked as awaiting manual review.

9. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 8, characterized in that, Using the identified thalweg point, the left bank floodplain-channel boundary point, and the right bank floodplain-channel boundary point, the river channel cross-section is divided into multiple roughness zones, specifically: The river channel is divided into the left bank floodplain area, the main channel area, and the right bank floodplain area, with the boundary between the left bank floodplain and the right bank floodplain as the boundary. Further subdivision of the main tank area: Using the thalweg point as a reference, the curvature of each cross-sectional measuring point within the main channel area is calculated point by point. The location with the largest absolute value of curvature within the main channel area to the left of the thalweg point is selected as the dividing point between the left side slope area and the main channel thalweg area. Within the main channel region to the right of the thalweg point, the location with the largest absolute value of curvature is selected as the dividing inflection point between the right-side slope area and the main channel thalweg area. Through the dividing inflection point and The main channel area is further subdivided into the left main channel slope area, the main channel deep channel area, and the right main channel slope area; Further subdivision of the left and right shoal areas: Starting from the boundary point between the river channel and the floodplain area that needs to be subdivided, calculate the single-step elevation rise between adjacent cross-sectional measuring points point by point in the direction away from the main channel area; if a certain cross-sectional measuring point If the elevation rise in two or more consecutive steps exceeds the preset threshold, then... Then and subsequent continuous single-step elevation rise exceeding the preset threshold The cross-sectional measurement points are recorded as sequence P; The first cross-sectional measurement point in sequence P This point was identified as a candidate dividing point. Obtain geomorphic feature descriptions of candidate boundary points and their adjacent cross-sectional measuring points. If the geomorphic features at the candidate boundary point change in type compared to the geomorphic features of the adjacent cross-sectional measuring points on the side closer to the main channel area, then the cross-validation is passed, and the candidate boundary point is determined as the boundary point between the near-channel beach and the far-channel high beach. The beach area that needs to be subdivided is further subdivided into the near-channel beach area and the far-channel high beach area through the beach boundary point. If cross-validation fails, the next section measurement point in sequence P is selected as the new candidate boundary point and cross-validation is performed again until cross-validation passes or sequence P is traversed. If no cross-sectional measurement point passes cross-validation after traversing sequence P, the candidate boundary point identified for the first time is used as the beach boundary point, and a prompt message is generated for manual confirmation.

10. The method for converting multi-source heterogeneous river cross-section data into a MIKE model according to claim 8, characterized in that: Physical rationality check: If the overall roughness of a certain roughness zone in a river cross section exceeds its corresponding reasonable range, or if the relative relationship between the overall roughness of each roughness zone violates the preset physical law, then the physical rationality check of the river cross section fails. Spatial consistency check: Calculate the comprehensive relative change rate of roughness of the same type of roughness partitions in adjacent river sections. If the comprehensive relative change rate of roughness of the same type of roughness partitions in two adjacent river sections exceeds the preset threshold, then mark the combination of adjacent river sections as failing the spatial consistency check.

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