CN112988945B - Prediction method and prediction system for river suspended pollutants - Google Patents
Prediction method and prediction system for river suspended pollutants Download PDFInfo
- Publication number
- CN112988945B CN112988945B CN202110445363.6A CN202110445363A CN112988945B CN 112988945 B CN112988945 B CN 112988945B CN 202110445363 A CN202110445363 A CN 202110445363A CN 112988945 B CN112988945 B CN 112988945B
- Authority
- CN
- China
- Prior art keywords
- point
- river
- curve
- central key
- river channel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000003344 environmental pollutant Substances 0.000 title claims abstract description 53
- 238000000034 method Methods 0.000 title claims abstract description 50
- 231100000719 pollutant Toxicity 0.000 title claims abstract description 47
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 35
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 238000011109 contamination Methods 0.000 claims description 19
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 16
- 239000003086 colorant Substances 0.000 claims description 12
- 239000000356 contaminant Substances 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 6
- 239000012895 dilution Substances 0.000 claims description 6
- 238000010790 dilution Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 5
- 230000008859 change Effects 0.000 abstract description 4
- 230000008569 process Effects 0.000 description 12
- 238000010586 diagram Methods 0.000 description 5
- 230000003068 static effect Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 3
- 238000011144 upstream manufacturing Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 239000010865 sewage Substances 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000003113 dilution method Methods 0.000 description 1
- 239000003651 drinking water Substances 0.000 description 1
- 235000020188 drinking water Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000006260 foam Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Entrepreneurship & Innovation (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for predicting river suspended pollutants, which comprises the steps of obtaining a first image map, and marking a first point on a river channel; marking a central key point of the river channel in the first image map based on the shape of the river channel; based on a central key point and a first point in the first image map, combining a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm to obtain a first curve; obtaining a trajectory curve based on the characteristics of the discharged pollutants, the river flow rate and the first curve; performing mathematical analysis on the second point and the third point based on the second point, the third point and the first curve to obtain a first vertical line and a second vertical line, wherein the area of the first vertical line and the second vertical line, which are used for intercepting the river, is a first area, and the first area is a river area polluted by pollutants in the river channel; the method has the advantages that a decision maker can intuitively recognize the pollution speed and the pollution area of the pollution conveniently, know the pollution degree change and conveniently make an emergency plan and a disposal measure in advance.
Description
Technical Field
The invention relates to the technical field of river regional treatment, in particular to a method and a system for predicting river suspended pollutants.
Background
Rivers are the most important water bodies on land, and large industrial areas and cities in the world are built on the sides of the rivers, and the rivers are used for supplying water and drinking water or utilizing the rivers for carrying goods. The improvement is opened, along with the rapid development of economy, the living standard of people is continuously improved, but the pollution condition of river water resources and environments is continuously worsened along with the development of economy. Some enterprises directly discharge water into rivers without good sewage treatment in the sewage discharge process, and some people directly discard domestic garbage and wastes in the rivers, so that the river pollution is caused.
In river pollutants, suspended matter pollution is a very common pollution form, and is represented by river turbidity, abnormal color on river surface, water foam and the like, and is accompanied by pungent peculiar smell, so that great damage to ecological environment is caused to river coasts, and even water problems are brought to surrounding residents, and great harm is caused.
However, in the conventional method for processing suspended matters in rivers, when a static pollution picture is drawn through image processing software, the following disadvantages exist: the static picture cannot deduce the pollution process, the pollution area and the pollution index depend on experience, the data reality degree is poor, the picture cannot be superposed with the real GIS river terrain and landform due to the static picture, the real geographic position contrast is lacked, and the deduction intuitiveness is not enough; when a pollution process animation is drawn through simulation or animation software, a pollution area and a pollution index depend on experience, the reality degree of data is poor, the animation mainly comprises gif animation, flash animation and video animation, the animation cannot be superposed with the real GIS river terrain and landform, the real geographic position contrast is lacked, and the derived intuitiveness is not enough; when the data is presented through a three-dimensional simulation system, the data is greatly limited by a platform and generally needs a three-dimensional engine for support, and when the data is applied, the configuration deduction can be carried out only by manually calculating each process parameter in advance, so that the data belongs to a semi-automatic technology, the calculation and deduction processes cannot be automatically carried out, and the expandability is poor.
Disclosure of Invention
The invention aims to provide a method and a system for predicting river suspended pollutants, which can process rivers in a two-dimensional map or a three-dimensional map by introducing an image map into a GIS platform, and can directly perform color division and presentation on a river pollution area by distinguishing pollution indexes by colors in the map, so that the intuitive observation on the river pollution change is realized.
The invention is realized by the following technical scheme:
a prediction method of river suspended pollutants comprises the following steps:
s1: acquiring a first image map, wherein the first image map is a plane image map of a river channel, and marking a first point on the river channel, wherein the first point is a pollutant discharge point;
s2: marking a plurality of central key points of the river channel in the first image map based on the shape of the river channel, wherein the central key points are central points on two sides of the river;
s3: based on a central key point and a first point in a first image map, and in combination with a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm, obtaining a first curve in the river channel, wherein the first curve is a flow trajectory curve with hydrodynamic characteristics;
s4: river flow velocity V based on the characteristics of the discharged pollutants1And a first curve, obtaining a trajectory curve between a second point and a third point, wherein the second point is a downstream central key point closest to the first point, and the third point is at T2At that moment, the contaminant diffuses into the water to a position furthest from the second point;
s5: and performing mathematical analysis on the second point and the third point based on the second point, the third point and the first curve to obtain a first vertical line and a second vertical line, wherein the first vertical line and the second vertical line are used for intercepting a river, and the first area is a river area polluted by pollutants in the river channel.
When the traditional diffusion prediction is carried out on suspended pollutants in rivers, static pictures or animation in the pollutant pollution process is drawn by simulation animation software, but when the river in the image is processed by adopting the technical method, the limitation of a platform is large, the true degree of data is not high, and the predicted river pollution area has a certain difference with the true value; the invention provides a method and a system for predicting river suspended pollutants, which are used for processing an acquired image map of a river, combining a mathematical algorithm with hydrodynamic curve characteristics in a vector river map, and matching relevant colors of pollution conditions in the river by combining a pollution index table, thereby realizing the visual display of the pollution conditions in a river area.
Preferably, the characteristic of the contaminant includes a dilution rate V of the contaminant in water2Contamination index B of the first point, contamination start time T1And the contamination end time T3。
Preferably, the prediction method further comprises:
dilution rate V based on parameter2Contamination index B of the first point, contamination start time T1And the contamination end time T3Extracting the contaminant at T2A pollution index at a moment C;
and matching the obtained pollution index C with the color code value in the pollution index table to obtain a first area with gradually changed colors.
Preferably, in step S4, the specific expression of the trajectory curve L is: l = P + V1*(T2-T1)
P is the position of the second point.
Preferably, the calculated expression of the pollution index C is:
C=B*(1-V2)^(T2-T1)，V2∈［0,1）
preferably, in step S2, the river course has a shape including a river curve state and a river branch shape, and the more complicated the river course shape is, the more central key points are marked.
Preferably, the specific operation of step S3 includes:
s31: obtaining a first central key point by using a Floyd shortest path method, wherein the first central key point is the central key point which is closest to the first point in the downstream direction of the river;
s32: obtaining m central key points in the downstream direction of the river channel by adopting a binary tree traversal method and taking the first central key point as a starting point, wherein m is less than n;
s33: and taking the first central key point as a starting point, adopting a Bezier curve algorithm in m central key points, sequentially connecting two adjacent central key points, and obtaining a first curve after connecting the m central key points, wherein the first curve is a flow track curve of hydrodynamic characteristics in the river channel.
Preferably, in step S5, the specific operation step of performing mathematical analysis on the second point and the third point includes:
obtaining a first tangent of a second point on the first curve and a second tangent of a third point on the first curve based on the hydrodynamic characteristic flow trajectory curve;
obtaining a first vertical line based on the first tangent line and the first curve, wherein the first vertical line is a straight line which is perpendicular to the first tangent line and intersects with the second point;
obtaining a second vertical line based on a second tangent line and the first curve, wherein the second vertical line is a straight line which is perpendicular to the second tangent line and intersects at a third point;
the river channel is segmented into a first area by the first vertical line and the second vertical line, and the first area is a river channel pollution area.
Preferably, the first image map is an image map loaded on a GIS map platform.
The invention also discloses a system for predicting river suspended pollutants, which comprises:
the GIS image map module is used for acquiring a first image map, wherein the first image map is a plane image map of the river channel, and marks a first point on the river channel, and the first point is a pollutant discharge point;
the point location marking module is used for marking central key points of the river channel in the first image maps based on the shape of the river channel, wherein the central key points are central points on two sides of the river;
the analysis processing module is used for obtaining a first curve in the river channel based on a central key point and a first point in the first image map and by combining a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm, wherein the first curve is a flow trajectory curve with hydrodynamic characteristics;
a distance calculation module for calculating a river flow velocity V based on characteristics of the discharged pollutants1And a first curve, obtaining a second point and a third point, wherein the second point is a downstream central key point which is closest to the first point, and the third point is at T2At that moment, the contaminant diffuses into the water to a position furthest from the second point;
and the region calculating and drawing module is used for obtaining a first region based on the second point, the third point and the first curve, wherein the first region is a river region polluted by pollutants in the river channel.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the invention adopts a prediction method and a prediction system of river suspended pollutants, can realize the treatment of river channels in a two-dimensional map or a three-dimensional map, and is compatible with a plurality of GIS application platforms;
2. a method and a system for predicting river suspended pollutants are characterized in that a hydrodynamic characteristic method and a mathematical algorithm are combined, an intuitive process of pollution change of pollution at different time is realized in a vector river map, a decision maker can intuitively recognize pollution speed and pollution areas of the pollution conveniently, and pollution degree change is known, so that emergency plans and disposal measures can be made in advance.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a schematic diagram of a prediction method;
FIG. 2 is a schematic diagram of a prediction system;
FIG. 3 is a schematic view of a first region;
fig. 4 is a diagram of bezier curves.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example one
A method for predicting river suspended pollutants, as shown in fig. 1, the steps of the prediction method include:
s1: acquiring a first image map, wherein the first image map is a plane image map of a river channel, and marking a first point on the river channel, wherein the first point is a pollutant discharge point;
the acquired first image map is obtained by loading a river and a nearby area on map platforms such as a hypergraph GIS platform, an ArcGIS platform or a QGIS platform, and forms a geographic information platform with a vector river map, and in the map, the river area can be overlaid by a river surface data map with particularly obvious colors, and the overlaid area with particularly obvious color features can be directly analyzed and processed.
S2: marking a plurality of central key points of the river channel in the first image map based on the shape of the river channel, wherein the central key points are central points on two sides of the river;
the center line of the river is drawn in the river region from the river region of the obtained river in the first video map, and the center key points of the river are set based on the drawn river center line, and the river center key points are classified according to the form of the river.
The river course morphology includes a river curve state and a river branch morphology, and the more complicated the river course morphology is, the more central key points are marked.
S3: based on a central key point and a first point in a first image map, and in combination with a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm, obtaining a first curve in the river channel, wherein the first curve is a flow trajectory curve with hydrodynamic characteristics;
the specific operation steps of step S3 include:
s31: obtaining a first central key point by using a Floyd shortest path method, wherein the first central key point is the central key point which is closest to the first point in the downstream direction of the river;
the Floyd algorithm is a classic dynamic programming algorithm. The method is an algorithm for solving the shortest path between any two points (called the multi-source shortest path problem), can correctly process the shortest path problem of a directed graph or a negative weight, and is mainly used for solving the position of a point closest to a pollution source through a Floyd shortest path algorithm.
The method adopting the Floyd shortest path comprises the following specific steps: acquiring the position coordinate of a pollution source point P; reading all central key points and corresponding position coordinates from a database; setting a temporary storage closest point ID, assigning the temporary storage closest point ID to be an initial point ID, and assigning the temporary storage shortest distance to be the maximum value of the floating point number; circulating all the central key points, and comparing the distances between the central key points and the coordinates of the pollution source point P one by one; comparing and temporarily storing the value of the shortest distance; if the current point distance is smaller than the temporary storage shortest distance value, updating the temporary storage closest point ID to be the current point ID, and updating the temporary storage shortest distance value to be the distance of the current point; and the cycle comparison is finished, and the last temporary storage closest point ID is the position point X closest to the pollution source point P, wherein the database is the place for storing all central key points.
S32: obtaining m central key points in the downstream direction of the river channel by adopting a binary tree traversal method and taking the first central key point as a starting point, wherein m is less than n;
the obtained m central key points are sequentially searched for the central key points through the front-back vector relation of the first central key point.
Traversal is one of the most important operations in the binary tree, and is the basis for performing other operations in the binary tree. The binary tree traversal is to round all the nodes of the binary tree according to a certain rule and order, and each node in the tree is accessed once and only accessed once in turn. In the application of binary tree traversal, the central key points are read out in a linear sequence manner, the central key points are traversed through the binary tree, the central key points along the downstream direction are sequentially obtained, and then the obtained central key points are sequentially processed.
The specific algorithm for binary tree traversal includes: establishing a process of searching downstream points according to the parameter points; reading all central key point data from a database, wherein the central key point data comprises a field current point ID and an upstream point ID; circularly traversing all the central key points, and comparing the ID of the upstream points of the circulating points according to the ID of the parameter points; if an ID matching the upstream point is found, the loop point is said to be a point downstream of the parameter point. After finding the downstream point, the circulation is not stopped, and a possible other downstream point is continuously searched until the point circulation is finished; connecting the parameter points with the found downstream points; and continuing to call the process, and taking the found downstream points as parameter points to be transmitted into the process.
S33: and taking the first central key point as a starting point, adopting a Bezier curve algorithm in m central key points, sequentially connecting two adjacent central key points, and obtaining a first curve after connecting the m central key points, wherein the first curve is a flow track curve of hydrodynamic characteristics in the river channel.
After finding a downstream adjacent central key point, forming a flow track of hydrodynamic characteristics of river current water flow by adopting a Bezier curve algorithm with the current central key point, and forming a flow track curve of hydrodynamic characteristics of the whole river behind a pollution source point by analogy, wherein the Bezier curve is a smooth curve drawn according to point coordinates of any position.
The specific algorithm for the Bezier curve algorithm is as follows: as shown in fig. 4, finding from the position of the pollution source point P to the downstream, and finding three adjacent central key points in sequence, wherein the three points are named as a point a, a point B, and a point C in sequence; finding points D and E on the AB and BC segments, such that AD/AB = BE/BC; connecting DE, finding point F on DE, F point needs to satisfy: DF/DE = AD/AB = BE/BC; and finding all F points according to the DE line segment and the calculation formula, and then connecting all the F points, namely the Bezier curve required by us. Generally, a value t is set, and the value range [0,1] of t represents the meaning of percentage, generally two digits are taken, and the distance from A to D, B to E, D to F in the graph is calculated according to an equal ratio from 0 to 1. And sequentially taking out decimal numbers from 0 to 1, wherein the decimal numbers generally take two or three digits, the decimal numbers can be determined according to actual conditions, and finally, all obtained F points in the corresponding sequence are sequentially drawn and connected to form a Bessel curve.
S4: river flow velocity V based on the characteristics of the discharged pollutants1And a first curve, obtaining a trajectory curve between a second point and a third point, wherein the second point is a downstream central key point closest to the first point, and the third point is at T2At that moment, the contaminant diffuses into the water to a position furthest from the second point;
the second point calculated here is where the contamination initially starts and the third point is where the contamination has spread to the furthest distance from the first point after a period of contamination.
In step S4, the specific expression of the trajectory curve L is:
L=P+V1*(T2-T1)
p is the position of the second point.
The characteristics of the pollutants comprise a dilution rate R2 of the pollutants in water, a pollution index B of a first point and a pollution starting time T1And the contamination end time T3
S5: and performing mathematical analysis on the second point and the third point based on the second point, the third point and the first curve to obtain a first vertical line and a second vertical line, wherein the first vertical line and the second vertical line are used for intercepting a river, and the first area is a river area polluted by pollutants in the river channel.
In step S5, the specific operation steps of performing mathematical analysis on the second point and the third point include:
obtaining a first tangent of a second point on the first curve and a second tangent of a third point on the first curve based on the hydrodynamic characteristic flow trajectory curve;
obtaining a first vertical line based on the first tangent line and the first curve, wherein the first vertical line is a straight line which is perpendicular to the first tangent line and intersects with the second point;
obtaining a second vertical line based on a second tangent line and the first curve, wherein the second vertical line is a straight line which is perpendicular to the second tangent line and intersects at a third point;
the river channel is segmented into a first area by the first vertical line and the second vertical line, and the first area is a river channel pollution area.
In the river region map, the first vertical line is calculated to divide the river region into two parts, and the second vertical line is calculated to divide a part of the river into two parts, so that the river region cut by separating the first vertical line from the second vertical line is the region where the river is polluted by pollutants discharged from the first point in the river.
Example two
The embodiment discloses a method for predicting river suspended pollutants, which is characterized in that on the basis of the first embodiment, a plurality of steps of a prediction method are added, and the added prediction method further comprises the following steps:
dilution rate V based on parameter2Contamination index B of the first point, contamination start time T1And the contamination end time T3Extracting the contaminant at T2A pollution index at a moment C;
and matching the obtained pollution index C with the color code value in the pollution index table to obtain a first area with gradually changed colors.
When pollutants are discharged into a river, the pollutants are diluted along with the flowing of water in the river, but in the dilution process, the river continuously flows towards the downstream direction, so the pollutants are continuously diffused and diluted towards the downstream direction of the river, pollution indexes corresponding to different central key points are different at different moments of pollutant discharge, the pollution index at each moment is calculated, the obtained pollution indexes are matched with the colors of corresponding pollution index tables, a regional diagram with gradually lighter colors in a river region from a second point to a third point in a first region is obtained, the darker colors represent that the pollution is more serious, and the lighter colors represent that the pollutants are already diluted.
After the pollution indexes are matched, converting the bezier curve into a filling path, and gradually filling the colors in the first area, that is, the depth of the colors can visually represent the pollution degree, as shown in fig. 3, which is a schematic diagram after the pollution area is marked.
The calculation expression of the pollution index C is as follows:
C=B*(1-V2)^(T2-T1)，V2∈［0,1）
EXAMPLE III
The embodiment discloses a system for predicting river suspended pollutants, as shown in fig. 2, which is a method for implementing the first embodiment or the second embodiment, and the system comprises:
the GIS image map module is used for acquiring a first image map, wherein the first image map is a plane image map of the river channel, and marks a first point on the river channel, and the first point is a pollutant discharge point;
a point location marking module for marking a central key point of the river channel in a plurality of first image maps based on the shape of the river channel, wherein the central key point is the central point of two sides of the river
The analysis processing module is used for obtaining a first curve in the river channel based on a central key point and a first point in the first image map and by combining a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm, wherein the first curve is a flow trajectory curve with hydrodynamic characteristics;
a distance calculation module for calculating a river flow velocity V based on characteristics of the discharged pollutants1And a first curve, obtaining a second point and a third point, wherein the second point is a downstream central key point which is closest to the first point, and the third point is at T2At all times, the contaminants are spreading in the waterDiverging to a position furthest from the second point;
and the region calculating and drawing module is used for obtaining a first region based on the second point, the third point and the first curve, wherein the first region is a river region polluted by pollutants in the river channel.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. A prediction method of river suspended pollutants is characterized by comprising the following steps:
s1: acquiring a first image map, wherein the first image map is a plane image map of a river channel, and marking a first point on the river channel, wherein the first point is a pollutant discharge point;
s2: marking a plurality of central key points of the river channel in the first image map based on the shape of the river channel, wherein the central key points are central points on two sides of the river;
s3: based on a central key point and a first point in a first image map, and in combination with a Floyd shortest path algorithm, a binary tree traversal algorithm and a Bezier curve algorithm, obtaining a first curve in the river channel, wherein the first curve is a flow trajectory curve with hydrodynamic characteristics;
the specific operation steps of step S3 include:
s31: obtaining a first central key point by using a Floyd shortest path method, wherein the first central key point is the central key point which is closest to the first point in the downstream direction of the river;
s32: obtaining m central key points in the downstream direction of the river channel by adopting a binary tree traversal method and taking the first central key point as a starting point, wherein m is less than n;
s33: taking a first central key point as a starting point, adopting a Bezier curve algorithm in m central key points, sequentially connecting two adjacent central key points, and obtaining a first curve after connecting the m central key points, wherein the first curve is a flow trajectory curve of hydrodynamic characteristics in a river channel;
s4: river flow velocity V based on the characteristics of the discharged pollutants1And a first curve, obtaining a trajectory curve between a second point and a third point, wherein the second point is a downstream central key point closest to the first point, and the third point is at T2At that moment, the contaminant diffuses into the water to a position furthest from the second point;
s5: and performing mathematical analysis on the second point and the third point based on the second point, the third point and the first curve to obtain a first vertical line and a second vertical line, wherein the first vertical line and the second vertical line are used for intercepting a river, and the first area is a river area polluted by pollutants in the river channel.
2. The method of claim 1, wherein the characteristic of the pollutant comprises a dilution rate V of the pollutant in water2Contamination index B of the first point, contamination start time T1And the contamination end time T3。
3. The method for predicting river suspended pollutants according to claim 2, further comprising:
dilution rate V based on parameter2Contamination index B of the first point, contamination start time T1And the contamination end time T3Extracting the contaminant at T2A pollution index at a moment C;
and matching the obtained pollution index C with the color code value in the pollution index table to obtain a first area with gradually changed colors.
4. The method for predicting river suspended pollutants according to claim 3, wherein in the step S4, the specific expression of the trajectory curve L is as follows:
L＝P+V1*(T2-T1)
p is the position of the second point.
5. The method for predicting river suspended pollutants according to claim 3, wherein the pollution index C is calculated by the following expression:
C＝B*(1-V2)^(T2-T1)，V2∈[0，1)。
6. the method for predicting river suspended pollutants according to claim 1, wherein in the step S2, the river channel morphology comprises a river curve state and a river bifurcation morphology, and the more complex the river channel morphology is, the more central key points are marked.
7. The method for predicting river suspended pollutants according to any one of claims 1 to 6, wherein the specific operation steps of performing mathematical analysis on the second point and the third point in the step S5 comprise:
obtaining a first tangent of a second point on the first curve and a second tangent of a third point on the first curve based on the hydrodynamic characteristic flow trajectory curve;
obtaining a first vertical line based on the first tangent line and the first curve, wherein the first vertical line is a straight line which is perpendicular to the first tangent line and intersects with the second point;
obtaining a second vertical line based on a second tangent line and the first curve, wherein the second vertical line is a straight line which is perpendicular to the second tangent line and intersects at a third point;
the river channel is segmented into a first area by the first vertical line and the second vertical line, and the first area is a river channel pollution area.
8. The method of any one of claims 7, wherein the first image map is an image map loaded on a GIS map platform.
9. A system for predicting river suspended pollutants, the system comprising:
the GIS image map module is used for acquiring a first image map, wherein the first image map is a plane image map of the river channel, and marks a first point on the river channel, and the first point is a pollutant discharge point;
the point location marking module is used for marking central key points of the river channel in the first image maps based on the shape of the river channel, wherein the central key points are central points on two sides of the river;
the analysis processing module is configured to obtain a first curve in the river based on a central key point and a first point in the first image map and by combining a Floyd shortest path algorithm, a binary tree traversal algorithm, and a bezier curve algorithm, where the first curve is a flow trajectory curve of hydrodynamic characteristics, and specifically includes:
obtaining a first central key point by using a Floyd shortest path method, wherein the first central key point is the central key point which is closest to the first point in the downstream direction of the river;
obtaining m central key points in the downstream direction of the river channel by adopting a binary tree traversal method and taking the first central key point as a starting point, wherein m is less than n;
taking a first central key point as a starting point, adopting a Bezier curve algorithm in m central key points, sequentially connecting two adjacent central key points, and obtaining a first curve after connecting the m central key points, wherein the first curve is a flow trajectory curve of hydrodynamic characteristics in a river channel;
a distance calculation module for calculating a river flow velocity V based on characteristics of the discharged pollutants1And a first curve, obtaining a second point and a third point, wherein the second point is a downstream central key point which is closest to the first point, and the third point is at T2At that moment, the contaminant diffuses into the water to a position furthest from the second point;
and the region calculating and drawing module is used for obtaining a first region based on the second point, the third point and the first curve, wherein the first region is a river region polluted by pollutants in the river channel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110445363.6A CN112988945B (en) | 2021-04-25 | 2021-04-25 | Prediction method and prediction system for river suspended pollutants |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110445363.6A CN112988945B (en) | 2021-04-25 | 2021-04-25 | Prediction method and prediction system for river suspended pollutants |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112988945A CN112988945A (en) | 2021-06-18 |
| CN112988945B true CN112988945B (en) | 2021-08-03 |
Family
ID=76340092
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110445363.6A Active CN112988945B (en) | 2021-04-25 | 2021-04-25 | Prediction method and prediction system for river suspended pollutants |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112988945B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115184568B (en) * | 2022-06-14 | 2023-04-18 | 河北省水利工程局集团有限公司 | Real-time monitoring method for river water environmental pollutants |
| CN118261336B (en) * | 2024-05-28 | 2024-08-13 | 江西怡杉环保股份有限公司 | Lake water pollution treatment method and system |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102608282A (en) * | 2011-01-21 | 2012-07-25 | 张波 | Water quality information computing device and method |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005173315A (en) * | 2003-12-12 | 2005-06-30 | Fuji Xerox Co Ltd | Toner for electrostatic charge image development, its manufacturing method, image forming method, and image forming method using the same |
| JP2010064002A (en) * | 2008-09-10 | 2010-03-25 | Kokusai Environmental Solutions Co Ltd | Method for estimating risk of groundwater contamination |
| CN104657783B (en) * | 2014-03-21 | 2016-03-30 | 北京千安哲信息技术有限公司 | For the section sliding-model control method of Mixing Coefficient in Rectangular Channels Release and dispersion prediction |
| CN105675448B (en) * | 2014-11-17 | 2018-07-03 | 中国科学院沈阳计算技术研究所有限公司 | A kind of method of dynamic analog pollutant diffusion monitored towards quality of water environment |
| CN104778356B (en) * | 2015-04-08 | 2017-06-16 | 重庆交通大学 | A kind of method for numerical simulation of Convention diffusion mass transport process |
| CN107403034B (en) * | 2017-06-28 | 2021-08-17 | 西交利物浦大学 | Water quality pollution diffusion early warning visualization method |
| CN111241758B (en) * | 2020-01-10 | 2022-09-20 | 燕山大学里仁学院 | Evaluation method based on transport and diffusion model of soluble pollutants in water environment |
| CN112633545A (en) * | 2020-07-14 | 2021-04-09 | 福州市环境科学研究院(福州市环境影响评价技术中心、福州市排污权储备技术中心) | Risk early warning method and system based on water pollution accident of Minjiang downstream |
| CN112508407B (en) * | 2020-12-07 | 2023-07-18 | 北京英视睿达科技股份有限公司 | Pollution tracing method based on water gene |
-
2021
- 2021-04-25 CN CN202110445363.6A patent/CN112988945B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102608282A (en) * | 2011-01-21 | 2012-07-25 | 张波 | Water quality information computing device and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112988945A (en) | 2021-06-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112988945B (en) | Prediction method and prediction system for river suspended pollutants | |
| Regnauld et al. | A synoptic view of generalisation operators | |
| Steinbrückner et al. | Representing development history in software cities | |
| CN110059264B (en) | Site retrieval method, equipment and computer storage medium based on knowledge graph | |
| CN110838153B (en) | Method for making modern inland river electronic channel chart based on ArcGIS system and application | |
| CN112765300A (en) | Water conservancy object relation map construction method based on ArcGIS spatial data | |
| CN105893632A (en) | Road name data compiling method and map labeling method and device | |
| Bucher et al. | Geoxygene: Built on top of the expertise of the french nma to host and share advanced gi science research results | |
| CN110688443A (en) | Map annotation model and annotation method thereof | |
| Regnauld* et al. | Creating a hydrographic network from its cartographic representation: a case study using Ordnance Survey MasterMap data | |
| CN116757004B (en) | EFDC three-dimensional water quality data multi-mode deduction method based on digital twin technology | |
| CN116846811A (en) | Optical fiber routing path planning method, system and medium based on district road | |
| CN111241228A (en) | Comprehensive drawing method based on vector data and graphical processing technology | |
| CN106651186A (en) | City planning management control processing method and system | |
| CN111091235A (en) | Method and device for determining incoming and outgoing line paths of substation area of transformer substation | |
| Maddison | Percolation Analysis | |
| CN111241221A (en) | Automatic matching and high-precision repairing method for damaged terrain coordinate data | |
| CN115934877B (en) | Generation method of ancient county level political region boundary map | |
| JPH10132200A (en) | Network tracking device, network tracking method, and recording medium | |
| Li et al. | Automatic method of flow direction reasoning for bridging tributaries using adjacency relation | |
| Rakićević | An Automated Process of Creating 3D City Model for Monitoring Urban Infrastructures | |
| Wadembere | Spatial Objects Management Method for Geodatabases | |
| Zenati et al. | Re-appropriation of urban heritage buildings and their role in the conservation of historic sites, case study: Casbah Belamech (Tindouf–Algeria) | |
| Sang | Visual Topology in SDI: A Data Structure for Modelling Landscape Perception | |
| CN118861048A (en) | Method for constructing dispatching physical water network by utilizing water conservancy object GIS feature analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |