A hydrological information sharing platform based on the Internet

Abstract

The invention discloses a hydrological information sharing platform based on the Internet, relates to the technical field of hydrological sharing on the Internet, and is used to solve the problems that the existing platform lacks an effective data verification mechanism, resulting in the adoption of erroneous or inaccurate data; and users often lack motivation to participate, feedback mechanisms or incentives, and fail to effectively evaluate the contribution and authority of users. The invention comprises a hydrological information acquisition unit, a hydrological information verification unit, a user analysis unit and a processing unit; an efficient and safe solution is provided by acquiring, verifying and analyzing hydrological data; the hydrological information verification unit uses geographic coordinate analysis to ensure the accuracy of the data, and then uses a digital elevation model to perform flow direction analysis to identify water area information and optimize water resource management; through accurate classification and matching of hydrological data, the efficiency of environmental monitoring and management is improved, and the effective use of hydrological resources by users at all levels is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet hydrological sharing, and in particular to a hydrological information sharing platform based on the Internet. Background Art

[0002] The sharing platform uses sensors and Internet technology to collect, transmit and analyze hydrological data in real time to support water resources management and environmental monitoring; hydrological information is data about water bodies and their dynamic changes, including water level, flow, rainfall, water temperature and water quality and other indicators; this information is not only used to monitor water resources, but also has important significance in areas such as water resources management, environmental protection and disaster warning, providing scientific basis for decision makers and helping to achieve sustainable development and ecological balance. However, the hydrological information sharing platform still has some defects: the lack of an effective data verification mechanism leads to the adoption of erroneous or inaccurate data; existing platform users often lack motivation to participate, lack feedback mechanisms or incentives; the existing platform fails to effectively evaluate the contribution and authority of users and other issues. Summary of the invention

[0003] The purpose of the present invention is to propose a hydrological information sharing platform based on the Internet in order to solve the problems that the existing platform lacks an effective data verification mechanism, resulting in the adoption of erroneous or inaccurate data; the existing platform users often lack the motivation to participate, lack feedback mechanisms or incentives; the existing platform fails to effectively evaluate the contribution and authority of users.

[0004] The object of the present invention can be achieved by the following technical solutions: a hydrological information sharing platform based on the Internet, comprising a hydrological information verification unit and a user analysis unit;

[0005] The hydrological information verification unit is used to verify and analyze the hydrological data in the database to be processed. The specific process is as follows:

[0006] Obtain geographical area features corresponding to geographical coordinates of detected hydrological data through the Internet; obtain boundary data of corresponding water areas in the database from the geographical area features; the boundary data is composed of polygon data or multi-point data, wherein the polygon data records the coordinates of each vertex of the water area boundary; and then convert the water area boundary into a geometric format to obtain a polygon;

[0007] Then use the vector space to analyze the hydrological data points to obtain the distance d between the point and the polygon; repeat the distance calculation and select the minimum value dmin, that is, the shortest distance from the point to the polygon; if the minimum distance dmin is less than the preset distance threshold, it is determined that the point belongs to the water area; otherwise, it is determined that the point does not belong to the water area; then the direction of the water flow is obtained by analyzing the flow direction of the raster data in the digital elevation model; then the flow accumulation of the grid unit is calculated to generate the flow matrix F(h, j); then the matching score S between the hydrological data point and the watershed is calculated; the matching score S is compared with the preset matching score threshold. If the matching score S is greater than the preset matching score threshold, the detection hydrological point belongs to the corresponding water area and watershed obtained in the networked geographic database; otherwise, a user score value reduction instruction is generated;

[0008] The user analysis unit is used to perform authority analysis and user rating value analysis on each user.

[0009] As a preferred embodiment of the present invention, it also includes a hydrological information acquisition unit and a processing unit;

[0010] The hydrological information acquisition unit acquires hydrological data through the Internet and stores it in a database to be processed, preliminarily classifies the acquired hydrological data according to the planning area or the natural geographical area, and then matches the hydrological data with corresponding rivers, reservoirs, lakes and other water areas according to the geographical location of the sensor or the acquisition point;

[0011] The processing unit processes the user comprehensive score and the user score decrease instruction, specifically: the user comprehensive score is processed, and the platform regularly issues rewards to users with high comprehensive score rankings; and souvenir labels are issued to high-scoring users;

[0012] When receiving a user rating decrease instruction, obtain a fixed rating decrease amount and remind the user.

[0013] As a preferred implementation of the present invention, the specific process of using the vector space to analyze the hydrological data points to obtain the distance d between the point and the polygon is:

[0014] For each hydrological data point to be processed, a ray is emitted to determine the number of intersections between it and the polygon boundary; if the number of intersections is an odd number, the point is inside the polygon; if it is an even number, the point is outside the polygon; if the hydrological data point is not inside the water polygon, the minimum distance between the point and the polygon is calculated, and a point P (x0, y0) and the two endpoints of the line segment A (x1, y1) and B (x2, y2) are set. The formula for calculating the distance from the point to the line segment is: , where d is the distance between the calculated point and the polygon.

[0015] As a preferred embodiment of the present invention, the specific process of performing flow direction analysis on the raster data in the digital elevation model to obtain the direction of the water flow is:

[0016] Initialize the digital elevation model and input the elevation data Z(h,j); the DEM grid data represents the elevation value of the surface for each grid cell; the grid cell size is Δx×Δy; determine the eight flow directions of each grid cell Z(h,j), and determine the flow direction according to the elevation value of its adjacent cells. The data Z in the figure is the central grid, and each direction is represented by a number; then calculate the flow direction, and flow from Z(h,j) to the direction with the smallest elevation difference between the adjacent grids Z(hi+x,j+y): , and compare to get the minimum dZ, which is taken as the direction of water flow.

[0017] As a preferred embodiment of the present invention, the specific process of authority analysis is as follows:

[0018] Quantify through literature citation rate, cooperation network, professional certification, and academic conference activities; obtain the literature citation number Cμ of user SMg based on the Internet, and then obtain the literature citation score YYZ by setting the citation rate standard;

[0019] Analyze the collaboration network, obtain the number of collaborations Nc between the user and other scholars, and calculate the coreness Ru of the academic collaboration network based on the user's influence in the collaboration network through PageRank or a similar PageRank algorithm. The coreness Ru is a value between 0 and 1. Assign [0,0.2) to 1, [0.2,0.4) to 2, [0.4,0.6) to 3, [0.6,0.8) to 4, and [0.8,1.0] to 5. Then the collaboration network score WPZ = Ru × 5.

[0020] Then, by counting the different types and corresponding numbers of industry certifications, honorary titles or awards obtained by users, the corresponding weight levels are set according to the corresponding levels of industry certifications, honorary titles or awards; Output the total honor score RYZ, A1v is the total number of industry certification levels, WA1v is the weight factor corresponding to the industry certification level, A2j is the total number of honorary title levels, WA2j is the weight factor corresponding to the honorary title level, A3l is the total number of award levels, WA3l is the weight factor corresponding to the award level;

[0021] Then count the number of times the user has participated in academic conferences and multiply it by the corresponding preset weight factor to get the academic conference score XSZ, including the number of speeches or the number of important positions held; finally, calculate the total authority score through the formula: Output the authority score QWZ, where ψ1, ψ2, ψ3 and ψ4 are all preset weight factors.

[0022] As a preferred implementation of the present invention, the specific process of the user rating value analysis is as follows:

[0023] The activity and contribution quality of users in the platform are obtained through the hydrological information acquisition unit; the activity is calculated by counting the frequency of users' activities, including the number of posts, comments, questions, and answers; the activity within a fixed time is calculated by the formula: Output the user's activity HYZ, where ft is the number of posts by the user, pl is the number of comments by the user, tw is the number of questions asked by the user, and hd is the number of questions answered by the user; χ1, χ2, χ3 and χ4 are all preset weight factors;

[0024] Contribution quality is based on different types of behavior including posting, commenting, asking questions, and answering; the formula is: Output the user's contribution quality score GXZ, ftp is the feedback evaluation value obtained by the user's posting, plp is the feedback evaluation value obtained by the user's comment posting, twp is the feedback evaluation value obtained by the user's question posting, and hdp is the feedback evaluation value obtained by the user's answer posting; χ5, χ6, χ7 and χ8 are all weights of the corresponding behaviors; then the user's activity score HYZ and the user's contribution quality score GXZ are comprehensively calculated to obtain the user score value YPZ, which is obtained by the formula Get, where θ4 and θ5 are the corresponding preset weights;

[0025] By formula Calculate the user's comprehensive rating value YZHZ, ε1 and 2 is the preset weight factor.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. The present invention provides an efficient and secure solution for the acquisition, verification and analysis of hydrological data by integrating sensors, data processing and geographic information systems. Users can access hydrological data such as rivers, lakes and rainfall in real time, and ensure the security of information through automatic data upload and encrypted transmission. The hydrological information verification unit uses geographic coordinate analysis to ensure the accuracy of the data, and then conducts flow direction analysis through digital elevation models (DEM) to improve the matching degree between data and actual water areas. It not only supports fast query and analysis, but also can effectively identify water area information, optimize water resources management, and ultimately provide scientific basis for decision makers to promote sustainable development. Through accurate classification and matching of hydrological data, the efficiency of environmental monitoring and management is improved, and the effective use of hydrological resources by users at all levels is promoted.

[0028] 2. The comprehensive authority and user rating value analysis of the user analysis unit of the present invention creates a transparent and effective user evaluation system for the platform; through real-name management and multi-dimensional scoring indicators (such as literature citations, cooperative networks, industry certifications, and user activity, etc.), it ensures that the user's influence and contribution quality are accurately quantified. This method not only encourages users to participate in and contribute high-quality content, but also promotes the sharing and dissemination of knowledge; in addition, through reward mechanisms (such as bonuses, badges, and user levels) and complaint channels, it enhances the user's sense of belonging and satisfaction, and continuously improves their professional influence; the comprehensive evaluation system creates a positive community atmosphere for the platform, promotes cooperation and communication among users, and provides reliable talent support for the sharing and application of hydrological information. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0030] Figure 1 It is a principle block diagram of the present invention;

[0031] Figure 2 Schematic diagram of grid unit size of the present invention. DETAILED DESCRIPTION

[0032] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0034] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0035] See also Figure 1As shown, a hydrological information sharing platform based on the Internet includes a hydrological information acquisition unit, a hydrological information verification unit, a user analysis unit and a processing unit;

[0036] The hydrological information acquisition unit obtains hydrological data through the Internet, and sensors (such as water level gauges, rain gauges, etc.) automatically monitor hydrological data such as rivers, lakes, and rainfall; the local gateway device then uploads the data to the sharing platform through the 4G / 5G network or Wi-Fi, and stores it in the database to be processed. Then, the collected hydrological data is preliminarily classified according to the planning area (such as province, city, county) or natural geographical area (such as river basin, mountain range, lake, etc.), and then the hydrological data is matched with the corresponding rivers, reservoirs, lakes and other water areas according to the geographical location of the sensor or collection point; for example, the data of a certain collection point is attributed to a specific river (such as the Yangtze River and the Yellow River) or reservoir; for larger rivers, the system can further subdivide the hydrological data according to the river basin or segment, such as the upper reaches, middle reaches, and lower reaches; each set of hydrological data will be assigned two key tags: regional tag and river water area tag; different databases or database tables are created according to the region or river water area, and the corresponding data is classified and stored for quick query and analysis; it should be noted that the data is encrypted during transmission to ensure security through encryption protocols (such as HTTPS);

[0037] The hydrological information verification unit is used to verify and analyze the hydrological data in the database to be processed. The specific process is as follows:

[0038] The geographical area characteristics corresponding to the geographical coordinates of the detected hydrological data are obtained through the Internet. The geographical area characteristics are obtained by obtaining the boundary data of the corresponding water areas (such as rivers, reservoirs, lakes, etc.) in the geographical database through networking; the boundary data is composed of polygon data or multi-point data, in which the polygon data records the coordinates of each vertex of the water area boundary; and then the water area boundary is converted into a geometric format: the boundary of each water area can be represented as a polygon formed by connecting multiple points, that is: , where x i ,y i are the coordinates of the boundary points;

[0039] Then, the hydrological data points are analyzed by using vector space to determine whether the hydrological data points are located within the boundary polygon of a certain water area; the vector space analysis is as follows: for each hydrological data point to be processed, a ray is emitted to determine the number of intersections between it and the polygon boundary; if the number of intersections is an odd number, the point is inside the polygon; if it is an even number, the point is outside the polygon;

[0040] If the hydrological data point is not within the water polygon, the minimum distance between the point and the polygon is calculated, and a point P (x0, y0) and two endpoints of the line segment A (x1, y1) and B (x2, y2) are set. The formula for calculating the distance from the point to the line segment is: , where d is the distance between the calculated point and the polygon; and repeat the distance calculation to select the minimum value dmin, that is, the shortest distance from the point to the polygon; if the minimum distance dmin is less than the preset distance threshold, it is determined that the point belongs to the water area; if the minimum distance dmin is greater than or equal to the preset distance threshold; it is determined that the point does not belong to the water area;

[0041] See also Figure 2 As shown, the flow direction is analyzed by the grid data in the digital elevation model (DEM), and matched with the hydrological data points and the watershed; the digital elevation model (DEM) is initialized and the elevation data Z(h,j) is input, where h and j represent the row and column indexes of the grid; the DEM grid data represents the elevation value of the surface for each grid cell, in meters; the grid cell size is Δx×Δy; then, eight flow directions are determined for each grid cell Z(h,j), and the flow direction is determined according to the elevation values ​​of its adjacent cells, and the data Z in the figure is the central grid, and each direction is represented by a number from 1 to 8: 1 represents northwest, 2 represents north, 3 represents northeast, 4 represents east, 5 represents southeast, 6 represents south, 7 represents southwest, and 8 represents west; then the flow direction is calculated, flowing from Z(h,j) to the direction with the smallest elevation difference between the adjacent grids Z(hi+x,j+y): , and compare to get the minimum dZ, and use this direction as the direction of water flow; finally, for each grid cell Z(h,j), compare the elevations of its eight neighboring grids, determine the direction of water flow and generate the flow direction matrix D(h,j), which ranges from 1 to 8, representing one of the eight directions; compare the flow direction matrix D(h,j) with the water flow direction of the text data point for consistency; if the flow directions are consistent, the matching degree is high;

[0042] Then calculate the flow accumulation of the grid cells. By setting the initial flow matrix F(h,j), the initial flow of each grid is set to 1 (indicating that each cell contributes at least one unit of flow); according to the flow direction matrix D(h,j), accumulate the flow from the upstream grid to the downstream; if the flow of grid Z (h,j) will flow into the grid pointed by the flow direction, update the flow F(h+x,j+y) of the inflow cell: , and repeatedly execute the updating inflow unit process until the flow of all grids is accumulated, and finally generate the flow matrix F(h,j); the accumulated flow matrix F(h,j) is compared with the hydrological data point to see whether it is in the high flow area of ​​the basin; if the F(h,j) value is large, the point is in the main river or tributary, and the matching degree is high;

[0043] If the F(h,j) value is small, the point is not in the main basin and the matching degree is low. Finally, the matching degree between the hydrological data point and the basin is calculated: Output the matching score S, where Fmax is the maximum cumulative flow value of all grid cells in the basin. When the F(h,j) value is close to Fmax, the matching degree approaches 1, and when F(h,j) is small, the matching degree approaches 0; d h,j is the distance between the hydrological data point and the center of the main river or tributary. h,j =0, it means that the hydrological data point is in the center of the river channel, and the position matching degree is 1; L is the flow angle between the flow matrix D(h,j) and the water flow direction of the hydrological data point, L∈[0,90]; a1, a2 and a3 are the preset weights corresponding to different parameters, which are set according to the specific application scenario; the matching score S is compared with the preset matching score threshold. If the matching score S is greater than the preset matching score threshold, the detected hydrological point belongs to the corresponding water area or basin obtained in the networked geographic database; otherwise, a user score value decrease instruction is generated;

[0044] The user analysis unit is used to perform authority analysis and user rating value analysis on each user. The specific process is as follows:

[0045] Through the real-name system for users, the real-name system users are numbered, SMg, g=1, 2, 3, ..., x; if the user refuses the real-name system or does not participate in the real-name system, the user is numbered separately, BMg;

[0046] Calculate the authority of a user SMg (authority is based on the user's influence in the field): quantify through literature citation rate, cooperation network, professional certification, academic conference activities, etc.; obtain the literature citation number Cμ of user SMg based on the Internet, and then set the citation rate standard, such as the total number of citations, to classify into different intervals, and assign values ​​according to the intervals: 0-100 citations, assigned a value of 1; 01-500 citations, assigned a value of 2, 501-1000 citations, assigned a value of 3, 1001-5000 citations, assigned a value of 4, 5000+ citations, assigned a value of 5; the formula is: Output the literature citation score YYZ, where 5000 is an empirical value, indicating that the score will reach the highest when the number of citations Cμ=5000. If the number of citations is greater than 5000, the highest score can only be 5 points. Then analyze the cooperation network, obtain the number of collaborations between the user and other scholars Nc, and calculate the core degree Ru of the academic cooperation network based on the user's influence in the cooperation network through PageRank or a similar PageRank algorithm. The core degree Ru is a value of 0-1; assign [0.0,0.2) to 1, [0.2,0.4) to 2, [0.4,0.6) to 3, [0.6,0.8) to 4, and [0.8,1.0] to 5; then the cooperation network score WPZ=Ru×5;

[0047] Then, by counting the different types and corresponding numbers of industry certifications, honorary titles or awards obtained by users, the corresponding weight levels are set according to the corresponding levels of industry certifications, honorary titles or awards; Output the total honor score RYZ, A1v is the total number of industry certification levels, WA1v is the weight factor corresponding to the industry certification level, A2j is the total number of honorary title levels, WA2j is the weight factor corresponding to the honorary title level, A3l is the total number of award levels, WA3l is the weight factor corresponding to the award level; v=1, 2, 3, ..., u; j=1, 2, 3, ..., m; l=1, 2, 3, ..., k; then count the number of times the user participates in academic conferences, and multiply it by the corresponding preset weight factor to get the academic conference score XSZ, including the number of speeches or the number of important positions; finally, calculate the total authority score by the formula: Output the authority score QWZ, where ψ1, ψ2, ψ3 and ψ4 are all preset weight factors;

[0048] Calculate the user rating for the same user SMg: obtain the activity and contribution quality of users in the platform through the hydrological information acquisition unit; the activity is calculated by counting the user's activity frequency, including the number of interactive behaviors such as posting, commenting, asking questions, and answering; the activity within a fixed time is calculated by the formula: Output the user's activity HYZ, where ft is the number of posts by the user, pl is the number of comments by the user, tw is the number of questions asked by the user, and hd is the number of questions answered by the user; χ1, χ2, χ3 and χ4 are all preset weight factors;

[0049] The quality of contribution is evaluated through the evaluation feedback of the content (such as likes, ratings, number of comments, etc.), and according to different types of behavior including posting, commenting, asking questions, answering, etc.; the formula is: Output the user's contribution quality score GXZ, where ftp is the feedback rating value obtained by the user's posting, plp is the feedback rating value obtained by the user's comment posting, twp is the feedback rating value obtained by the user's question posting, and hdp is the feedback rating value obtained by the user's answer posting; χ5, χ6, χ7 and χ8 are the weights of the corresponding behaviors, indicating the degree of influence of each behavior on the contribution quality; the feedback rating values ​​of ft, pl, tw, and hd are all calculated by the formula Output feedback evaluation value FKp (FKp is a general term for ftp, plp, twp, hdp), dzs is the total number of likes, pfs is the mean score, lps is the mean comment feedback, θ1, θ2 and θ3 are the corresponding preset weights;

[0050] Then the user's activity score HYZ and the user's contribution quality score GXZ are comprehensively calculated to obtain the user score value YPZ, which is calculated by the formula Get, where θ4 and θ5 are the corresponding preset weights;

[0051] The user analysis unit is also used to perform a comprehensive calculation on the QWZ obtained after the authority analysis and the YPZ obtained after the user rating value analysis to obtain the user comprehensive rating value YZHZ, which is calculated by the formula We get, where ε1 and 2 is the preset weight factor;

[0052] The processing cell processes the user's comprehensive rating value and the user's rating value decrease instruction, specifically:

[0053] Process the comprehensive score of users, and the platform will regularly issue rewards to users with high comprehensive scores; and issue souvenir labels to high-scoring users; display them in their personal profiles to mark their achievements, such as "top contributor" and "gold medal answerer", etc.; set user levels, and as the comprehensive score increases, users can unlock higher levels and obtain corresponding identity tags, etc.;

[0054] When receiving a user rating decrease instruction, obtain a fixed rating decrease amount and remind the user; users can file an appeal, including online forms and customer service support; online form: users fill out the appeal form, explain the reason and provide evidence; customer service support: provide a way to contact customer service for manual appeal; if the appeal is approved, restore the user's rating and notify the user; if the appeal is not approved, explain the reason to the user and provide improvement suggestions again.

[0055] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A hydrological information sharing platform based on the Internet, comprising a hydrological information verification unit and a user analysis unit, characterized in that: The hydrological information verification unit is used to verify and analyze the hydrological data in the database to be processed. The specific process is as follows: Obtain geographical area features corresponding to geographical coordinates of detected hydrological data through the Internet; obtain boundary data of corresponding water areas in the database from the geographical area features; the boundary data is composed of polygon data or multi-point data, wherein the polygon data records the coordinates of each vertex of the water area boundary; and then convert the water area boundary into a geometric format to obtain a polygon; Then use the vector space to analyze the hydrological data points to obtain the distance d between the point and the polygon; Repeat the distance calculation and select the minimum value dmin, that is, the minimum distance from the point to the polygon; if the minimum distance dmin is less than the preset distance threshold, it is determined that the point belongs to the water area; otherwise, it is determined that the point does not belong to the water area; then the direction of the water flow is obtained by analyzing the flow direction of the raster data in the digital elevation model; then the flow accumulation of the grid unit is calculated to generate the flow matrix F(h, j); then the matching score S between the hydrological data point and the watershed is calculated; the matching score S is compared with the preset matching score threshold, if the matching score S is greater than the preset matching score threshold, the detection hydrological point belongs to the corresponding water area and watershed obtained in the networked geographic database; otherwise, a user score value reduction instruction is generated; The user analysis unit is used to perform authority analysis and user rating value analysis on each user.

2. The Internet-based hydrological information sharing platform according to claim 1, characterized in that: It also includes a hydrological information acquisition unit and a processing unit; The hydrological information acquisition unit acquires hydrological data through the Internet and stores it in a database to be processed, preliminarily classifies the acquired hydrological data according to the planning area or the natural geographical area, and then matches the hydrological data with corresponding rivers, reservoirs, lakes and other water areas according to the geographical location of the sensor or the acquisition point; The processing unit processes the user comprehensive score and the user score decrease instruction, specifically: the user comprehensive score is processed, and the platform regularly issues rewards to users with high comprehensive score rankings; and souvenir labels are issued to high-scoring users; When receiving a user rating decrease instruction, obtain a fixed rating decrease amount and remind the user.

3. The Internet-based hydrological information sharing platform according to claim 1 is characterized in that: The specific process of using vector space to analyze the hydrological data points to obtain the distance d between the points and the polygons is: For each hydrological data point to be processed, a ray is emitted to determine the number of intersections between it and the polygon boundary; If the intersection point is an odd number, then the point is inside the polygon; if it is an even number, then the point is outside the polygon; If the hydrological data point is not within the water polygon, the minimum distance between the point and the polygon is calculated, and a point P (x0, y0) and two endpoints of the line segment A (x1, y1) and B (x2, y2) are set. The formula for calculating the distance from the point to the line segment is: , where d is the distance between the calculated point and the polygon.

4. The Internet-based hydrological information sharing platform according to claim 3 is characterized in that: The specific process of performing flow direction analysis on the raster data in the digital elevation model to obtain the direction of the water flow is as follows: Initialize the digital elevation model and input the elevation data Z(h,j); the DEM grid data represents the elevation value of the surface for each grid cell; the grid cell size is Δx×Δy; determine the eight flow directions of each grid cell Z(h,j), and determine the flow direction according to the elevation value of its adjacent cells. The data Z in the figure is the central grid, and each direction is represented by a number; then calculate the flow direction, and flow from Z(h,j) to the direction with the smallest elevation difference between the adjacent grids Z(hi+x,j+y): , and compare to get the minimum dZ, which is taken as the direction of water flow.

5. The Internet-based hydrological information sharing platform according to claim 1 is characterized in that: The specific process of authoritative analysis is as follows: Quantify through literature citation rate, cooperation network, professional certification, and academic conference activities; obtain the literature citation number Cμ of user SMg based on the Internet, and then obtain the literature citation score YYZ by setting the citation rate standard; Analyze the collaboration network, obtain the number of collaborations Nc between the user and other scholars, and calculate the coreness Ru of the academic collaboration network based on the user's influence in the collaboration network through PageRank or a similar PageRank algorithm. The coreness Ru is a value between 0 and 1. Assign [0,0.2) to 1, [0.2,0.4) to 2, [0.4,0.6) to 3, [0.6,0.8) to 4, and [0.8,1.0] to 5. Then the collaboration network score WPZ = Ru × 5. Then, by counting the different types and corresponding numbers of industry certifications, honorary titles or awards obtained by users, the corresponding weight levels are set according to the corresponding levels of industry certifications, honorary titles or awards; Output the total honor score RYZ, A1v is the total number of industry certification levels, WA1v is the weight factor corresponding to the industry certification level, A2j is the total number of honorary title levels, WA2j is the weight factor corresponding to the honorary title level, A3l is the total number of award levels, WA3l is the weight factor corresponding to the award level; Then count the number of times the user has participated in academic conferences and multiply it by the corresponding preset weight factor to get the academic conference score XSZ, including the number of speeches or the number of important positions held; finally, calculate the total authority score through the formula: Output the authority score QWZ, where ψ1, ψ2, ψ3 and ψ4 are all preset weight factors.

6. The Internet-based hydrological information sharing platform according to claim 5, characterized in that: The specific process of the user rating value analysis is as follows: The activity and contribution quality of users in the platform are obtained through the hydrological information acquisition unit; the activity is calculated by counting the frequency of users' activities, including the number of posts, comments, questions, and answers; The activity within a fixed time is calculated by the formula: Output the user's activity HYZ, where ft is the number of posts by the user, pl is the number of comments by the user, tw is the number of questions asked by the user, and hd is the number of questions answered by the user; χ1, χ2, χ3 and χ4 are all preset weight factors; Contribution quality is based on different types of behavior including posting, commenting, asking questions, and answering; the formula is: Output the user's contribution quality score GXZ, ftp is the feedback evaluation value obtained by the user's posting, plp is the feedback evaluation value obtained by the user's comment posting, twp is the feedback evaluation value obtained by the user's question posting, and hdp is the feedback evaluation value obtained by the user's answer posting; χ5, χ6, χ7 and χ8 are all weights of the corresponding behaviors; then the user's activity score HYZ and the user's contribution quality score GXZ are comprehensively calculated to obtain the user score value YPZ, which is obtained by the formula Get, where θ4 and θ5 are the corresponding preset weights; By formula Calculate the user's comprehensive rating value YZHZ, ε1 and 2 is the preset weight factor.

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