CN118171908A - Geological disaster risk evaluation method - Google Patents
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Abstract
The invention relates to the technical field of geological disaster monitoring, and discloses a geological disaster risk evaluation method, which comprises the following steps: s1, generating a tiff layer based on rainfall of set time; s2, carrying out quantitative analysis on stratum lithology, earthquake intensity, landform and terrain gradient, and calculating a geological landslide early warning index Q j of the region by combining rainfall of set time; s3, geological disaster early warning and grading of set time are generated: grading the geological disaster monitoring and early warning according to the value of the geological landslide early warning index Q j and generating a geological disaster early warning tiff image layer; s4, generating geological disaster early warning vector data of set time: and converting the geological disaster early warning tiff raster data of the set time into shp vector data. The method solves the problems that the probability of occurrence of the geological disaster is difficult to comprehensively judge, the geological disaster risk of the hydropower station is difficult to accurately reflect and the like in the prior art.
Description
Technical Field
The invention relates to the technical field of geological disaster monitoring, in particular to a geological disaster risk evaluation method.
Background
The hydropower station has the characteristics of large drainage basin range, large drainage basin area and complex geological structure. Thus, a hydropower station often spans different topography units, regional geologic structure units, formation lithology units, hydrogeologic units, and so forth. The geological disaster risk evaluation work is always used as a preliminary topic of the feasibility research of the hydropower engineering, the research on the aspects of engineering geological condition investigation and evaluation, regional geological disaster regularity research evaluation and risk control of the hydropower engineering and the like of the hydropower engineering are not developed in China, and unified standards and methods for site geological disaster evaluation and risk control of the hydropower engineering are lacking.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a geological disaster risk evaluation method, which solves the problems that the probability of occurrence of geological disasters is difficult to comprehensively judge, the geological disaster risk of a hydropower station is difficult to accurately reflect and the like in the prior art.
The invention solves the problems by adopting the following technical scheme:
A geological disaster risk evaluation method comprises the following steps:
S1, generating a tiff layer based on rainfall of set time;
s2, carrying out quantitative analysis on stratum lithology, earthquake intensity, landform and terrain gradient, and calculating a geological landslide early warning index Q j of the region by combining rainfall of set time;
s3, geological disaster early warning and grading of set time are generated: grading the geological disaster monitoring and early warning according to the value of the geological landslide early warning index Q j and generating a geological disaster early warning tiff image layer;
S4, generating geological disaster early warning vector data of set time: and converting the geological disaster early warning tiff raster data of the set time into shp vector data.
In step S1, the original rainfall data of the future set time is obtained through a third party data platform, an engineering file and a data source are created through a third party development library GDAL, the original rainfall tiff image is created based on a GDAL component library, the image projection is converted into a mercerized WGS84 through GDAL, the re-classification of the WGS84 image is performed according to the region, the contour line is extracted from the re-classified image, the contour line is converted into an isosurface, and then the contour surface is cut according to the isosurface to generate the tiff image layer of the rainfall of the future set time.
As a preferable technical solution, in step S2, a calculation formula of the regional geological landslide early-warning index Q j is:
Q j = stratum lithology grading factor + seismic intensity grading factor · 5/8+ landform grading factor · 7/8+ terrain gradient factor/2 + rainfall · 5/8.
As a preferable technical solution, in step S2, the method for quantifying the formation lithology grading coefficient is as follows:
the engineering geological rock group is loose soil, and the stratum lithology grading coefficient is defined as 0.177;
Engineering geological rock groups are invasive rock, and stratum lithology grading coefficients are defined as 0.052;
the engineering geological rock group is blocky metamorphic rock, and the stratum lithology grading coefficient is defined as 0.061;
the engineering geological rock group is the sprayed rock, and the stratum lithology grading coefficient is defined as 0.077;
the engineering geological rock group is clastic rock, and the stratum lithology grading coefficient is defined as 0.219;
The engineering geological rock group is sheet or plate metamorphic rock, and the stratum lithology grading coefficient is defined as 0.199;
The engineering geological rock group is carbonate rock, and the stratum lithology grading coefficient is defined as 0.091;
The engineering geological rock group is collapsible loess, and the stratum lithology grading coefficient is defined as 0.124.
The earthquake intensity quantification method comprises the following steps:
the seismic intensity is less than VI, and the seismic intensity grading coefficient is 0.06;
VI is less than or equal to seismic intensity and less than VII, and the seismic intensity grading coefficient is 0.121;
VII is less than or equal to seismic intensity and less than VIII, and the seismic intensity grading coefficient is 0.223;
VIII is less than or equal to seismic intensity and less than IX, and the seismic intensity grading coefficient is 0.277;
The seismic intensity is larger than or equal to IX, and the seismic intensity grading coefficient is 0.319.
The landform quantization method comprises the following steps:
the landform is plain, and the grading coefficient of the landform is 0.062;
The landform is hilly, and the grading coefficient of the landform is 0.085;
The landform is extremely high mountain, and the grading coefficient of the landform is 0.093;
The landform is mountain, and the grading coefficient of the landform is 0.106;
the landform is a plateau, and the grading coefficient of the landform is 0.135;
The landform is a low mountain, and the grading coefficient of the landform is 0.214;
the relief is a Zhongshan and the grading coefficient of the relief is 0.305.
The terrain gradient quantization method comprises the following steps:
the gradient is less than or equal to 15 degrees, and the gradient coefficient is 0.1;
15 DEG < gradient less than or equal to 25 DEG, and gradient coefficient is 0.219;
Gradient >40 °, gradient coefficient 0.244;
25 DEG < gradient less than or equal to 40 DEG, and gradient coefficient is 0.437.
In the step S3, the geological disaster monitoring and early warning grade is divided into four grades of red, orange, yellow and green, wherein the red early warning indicates that the geological landslide early warning index is more than or equal to 0.195; the orange early warning indicates that the early warning index of the geological landslide is more than or equal to 0.193 and less than 0.195; yellow early warning means that the early warning index of the geological landslide is more than or equal to 0.177 and less than 0.193; the green early warning indicates that the geological landslide early warning index is less than 0.177.
As a preferred technical solution, step S4 includes the following steps:
S41, binarizing the image;
S42, preprocessing the binary image;
s43, thinning: gradually stripping the points of the outline edge from the binary image pixel array to enable the binary image pixel array to be a skeleton pattern with a line width of only one pixel;
s44, tracking: converting the skeleton into a coordinate sequence of a vector graph;
S45, topological: and finding out the end points, nodes and isolated points of the line, and carrying out topology on the image.
As a preferred embodiment, step S43 includes the steps of:
s431, determining a pixel set to be refined;
s432, removing the pixel element which is not a skeleton;
s433, repeating S432 until only skeleton pixel remains.
As a preferred technical solution, step S44 includes the following steps:
S441, drawing a starting point along a search line and recording coordinates;
s442, tracking points in 8 directions of the starting point, if no point is tracked in 8 directions, finishing tracking the line, and returning to S441 to track the next line; if the tracking point is found, the coordinates of the tracking point are recorded;
s443, taking the point tracked in the step S422 as a new starting point, returning to the step S442, and continuously tracking 8 directions of the starting point; until connected into a boundary arc segment.
As a preferable embodiment, the set time is 24 hours or 72 hours.
As a preferred technical scheme, the method further comprises the following steps:
And S5, issuing a geological disaster early warning map service for a set time, and comprehensively displaying the geological disaster risk evaluation vector data of the hydropower station.
Compared with the prior art, the invention has the following beneficial effects:
According to the method, the possibility of occurrence of the geological disaster is comprehensively judged according to the monitoring data, the early warning model and the macroscopic phenomenon, the geological disaster risk of the hydropower station can be accurately reflected, and the management and control capacity of the geological disaster risk of the hydropower station is improved.
Drawings
FIG. 1 is a flow chart of an evaluation method for evaluating the risk of a geological disaster of a hydropower station according to the invention;
FIG. 2 is a schematic diagram of isolated points that are topologically implemented;
FIG. 3 is a schematic diagram of an endpoint for topology;
fig. 4 is a schematic diagram of nodes undergoing topology.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but embodiments of the present invention are not limited thereto.
Example 1
As shown in fig. 1 to 4, the invention discloses a hydropower station-based geological disaster risk evaluation method, which comprises the following steps: s1, generating a tiff image layer based on rainfall of 24/72 hours in the future;
S2, calculating an early warning index Q j of regional geological landslide; s3, generating 24/72 hour geological disaster early warning and grading; s4, generating geological disaster early warning vector data of 24/72 hours: converting the geological disaster early warning tiff raster data of 24/72 hours into shp vector data; s5, geological disaster early warning display for 24/72 hours: and (3) comprehensively displaying the geological disaster risk evaluation vector data of the hydropower station in the GIS platform through the ArcGISServer software release 24/72 hours geological disaster early warning map service. According to the method, the possibility of occurrence of the geological disaster is comprehensively judged according to the monitoring data, the early warning model and the macroscopic phenomenon, the geological disaster risk of the hydropower station can be accurately reflected, and the management and control capacity of the geological disaster risk of the hydropower station is improved.
The invention aims to overcome the defects of the prior art and provide the hydropower station geological disaster risk evaluation method for comprehensively judging the occurrence possibility of geological disasters according to monitoring data, an early warning model and macroscopic phenomena, so that the geological disaster risk of the hydropower station can be accurately reflected, and the geological disaster risk management and control capability of the hydropower station is improved.
The aim of the invention is realized by the following technical scheme:
A geological disaster risk evaluation method based on a hydropower station comprises the following steps:
S1, generating a tiff image layer based on the rainfall of 24/72 hours in the future: acquiring original rainfall data of 24/72 hours in the future through a third party data platform, creating engineering files and data sources through a third party development library GDAL, creating original rainfall tiff images based on a GDAL component library by reading the rainfall data, converting the image projection into a cutterhead to change WGS84 through GDAL, reclassifying the WGS84 images of the rainfall according to each province, carrying out contour line extraction on the reclassified images, converting the contour lines into contour surfaces, and then cutting according to the contour surfaces to generate tiff images of the rainfall of 24/72 hours in the future;
S2, carrying out quantitative analysis on influence factors such as stratum lithology, earthquake intensity, landform and terrain gradient, and calculating regional geological landslide early warning index Q j by adopting a hierarchical analysis method in combination with 24/72 hour rainfall:
q j = stratum lithology grading factor + seismic intensity grading factor · 5/8+ landform grading factor · 7/8+ terrain gradient factor/2 + rainfall · 5/8.
S3, generating 24/72 hour geological disaster early warning and grading: according to the value of the geological landslide early warning index Q j, the geological disaster monitoring early warning grade is classified into four grades of red, orange, yellow and green: generating a geological disaster early warning tiff image layer based on the generated geological disaster monitoring early warning, and extracting contour lines of early warning data through GDAL components;
s4, generating geological disaster early warning vector data of 24/72 hours: converting the geological disaster early warning tiff raster data of 24/72 hours into shp vector data;
S5, geological disaster early warning display for 24/72 hours: and (3) comprehensively displaying the geological disaster risk evaluation vector data of the hydropower station in the GIS platform through the ArcGISServer software release 24/72 hours geological disaster early warning map service.
Example 2
As further optimization of embodiment 1, as shown in fig. 1 to 4, this embodiment further includes the following technical features on the basis of embodiment 1:
As shown in fig. 1, the method for evaluating the geological disaster risk based on the hydropower station provided by the invention comprises the following steps:
S1, generating a tiff image layer based on the rainfall of 24/72 hours in the future: acquiring original rainfall data of 24/72 hours in the future through a third party data platform, creating engineering files and data sources through a third party development library GDAL, creating original rainfall tiff images based on a GDAL component library by reading the rainfall data, converting the image projection into a cutterhead to change WGS84 through GDAL, reclassifying the WGS84 images of the rainfall according to each province, carrying out contour line extraction on the reclassified images, converting the contour lines into contour surfaces, and then cutting according to the contour surfaces to generate tiff images of the rainfall of 24/72 hours in the future;
S2, carrying out quantitative analysis on influence factors such as stratum lithology, earthquake intensity, landform and terrain gradient, and calculating regional geological landslide early warning index Q j by adopting a hierarchical analysis method in combination with 24/72 hour rainfall:
q j = stratum lithology grading factor + seismic intensity grading factor · 5/8+ landform grading factor · 7/8+ terrain gradient factor/2 + rainfall · 5/8.
(1) The stratum lithology quantification method comprises the following steps:
The engineering geological rock group is loose soil, the grade is defined as 1, and the stratum lithology grading coefficient is defined as 0.177;
engineering geological rock groups are invasive rock, the grade is defined as 2, and the stratum lithology grading coefficient is defined as 0.052;
the engineering geological rock group is blocky metamorphic rock, the grade is defined as 3, and the stratum lithology grading coefficient is defined as 0.061;
Engineering geological rock groups are jet rocks, the grade is defined as 4, and the stratum lithology grading coefficient is defined as 0.077;
The engineering geological rock group is clastic rock, the grade is defined as 5, and the stratum lithology grading coefficient is defined as 0.219;
The engineering geological rock group is slice-shaped and plate-shaped metamorphic rock, the grade is defined as 6, and the stratum lithology grading coefficient is defined as 0.199;
The engineering geological rock group is carbonate rock, the grade is defined as 7, and the stratum lithology grading coefficient is defined as 0.091;
the engineering geological rock group is collapsible loess, the grade is defined as 8, and the stratum lithology grading coefficient is defined as 0.124.
(2) The earthquake intensity quantification method comprises the following steps:
The seismic intensity is less than VI, the grade is defined as 1, and the seismic intensity grading coefficient is 0.06;
VI is less than or equal to seismic intensity and less than VII, the grade is defined as 2, and the seismic intensity grading coefficient is 0.121;
VII is less than or equal to seismic intensity and less than VIII, the grade is defined as 3, and the seismic intensity grading coefficient is 0.223;
VIII is less than or equal to seismic intensity and less than IX, the grade is defined as 4, and the seismic intensity grading coefficient is 0.277;
the seismic intensity is larger than or equal to IX, the grade is defined as 5, and the seismic intensity grading coefficient is 0.319.
(3) The landform quantization method comprises the following steps:
The landform is plain, the grade is defined as 1, and the grading coefficient of the landform is 0.062;
The landform is hilly, the grade is defined as 2, and the grading coefficient of the landform is 0.085;
The landform is extremely high mountain, the grade is defined as 3, and the grading coefficient of the landform is 0.093;
The landform is mountain, the grade is defined as 4, and the grading coefficient of the landform is 0.106;
the landform is a plateau, the grade is defined as 5, and the grading coefficient of the landform is 0.135;
The landform is a low mountain, the grade is defined as 6, and the grading coefficient of the landform is 0.214;
The relief is a mountain, the grade is defined as 7, and the relief grading coefficient is 0.305.
(4) The terrain gradient quantization method comprises the following steps:
Grade is less than or equal to 15 degrees, grade is defined as 1, and grade coefficient is 0.1;
15 DEG < gradient less than or equal to 25 DEG, grade is defined as 2, gradient coefficient is 0.219;
grade > 40 deg., grade defined as 3, grade coefficient 0.244;
25 DEG < gradient less than or equal to 40 DEG, grade is defined as 4, gradient coefficient is 0.437.
S3, generating 24/72 hour geological disaster early warning and grading: according to the value of the geological landslide early warning index Q j, the geological disaster monitoring early warning grade is classified into four grades of red, orange, yellow and green: generating a geological disaster early warning tiff image layer based on the generated geological disaster monitoring early warning, and extracting contour lines of early warning data through GDAL components; the red early warning (warning level) shows that the possibility of occurrence of geological disasters is high, and the geological landslide early warning index Q j is more than or equal to 0.195; orange early warning (early warning level) indicates that the possibility of occurrence of geological disasters is high; geological landslide early warning index Q j is more than or equal to 0.193 and less than 0.195; yellow early warning (attention level) indicates that geological disasters are more likely to occur; geological landslide early warning index Q j is more than or equal to 0.177 and less than 0.193; the green early warning (general level) shows that the possibility of occurrence of geological disasters is small, and the geological landslide early warning index Q j is smaller than 0.177.
S4, generating geological disaster early warning vector data of 24/72 hours: converting the geological disaster early warning tiff raster data of 24/72 hours into shp vector data; the method specifically comprises the following substeps:
s41, binarizing the image; since the scanned images are stored in different gray levels, two stages (0 and 1) are needed for the conversion of the raster data vector, called binarization;
s42, preprocessing the binary image: due to unclean manuscript, some white fly, stain, rough line edge, etc. may appear in the image, and the input image is smoothed to remove the noise, thus laying a foundation for further refinement;
s43, thinning (peeling method and skeleton method): gradually stripping the points of the contour edge from the binary image pixel array to form a skeleton pattern with a line width of only one pixel; the basic process of refinement is:
s431, determining a pixel set to be refined;
s432, removing the pixel element which is not a skeleton;
s433, repeating S432 until only skeleton pixel remains;
S44, tracking: the thinned binary image forms a skeleton diagram, and the skeleton is converted into a coordinate sequence of a vector diagram by tracking; the basic steps are as follows:
S441, drawing a starting point along a search line from left to right and from top to bottom, and recording coordinates;
s442, tracking points in 8 directions of the starting point, if no point is tracked in 8 directions, finishing tracking the line, and returning to S441 to track the next line; if the tracking point is found, the coordinates of the tracking point are recorded;
S443, returning to S442 by taking the point tracked by S422 as a new starting point, and continuing to track 8 directions of the starting point; until connected into a boundary arc section;
s45, topological: finding out the end points and nodes of the line and isolated points, and carrying out topology on the image;
The isolated points refer to the pixels without 1 in the 8-neighbor city, as shown in fig. 2; the endpoint refers to that only one pixel with 1 in the 8 adjacent city is shown in fig. 3; the nodes refer to three or more than three 1 pixels in the 8-neighbor city, as shown in fig. 4.
S5, geological disaster early warning display for 24/72 hours: and (3) comprehensively displaying the geological disaster risk evaluation vector data of the hydropower station in the GIS platform through the ArcGISServer software release 24/72 hours geological disaster early warning map service.
As described above, the present invention can be preferably implemented.
All of the features disclosed in all of the embodiments of this specification, or all of the steps in any method or process disclosed implicitly, except for the mutually exclusive features and/or steps, may be combined and/or expanded and substituted in any way.
The foregoing description of the preferred embodiment of the invention is not intended to limit the invention in any way, but rather to cover all modifications, equivalents, improvements and alternatives falling within the spirit and principles of the invention.
Claims (10)
1. The geological disaster risk evaluation method is characterized by comprising the following steps of:
S1, generating a tiff layer based on rainfall of set time;
s2, carrying out quantitative analysis on stratum lithology, earthquake intensity, landform and terrain gradient, and calculating a geological landslide early warning index Q j of the region by combining rainfall of set time;
s3, geological disaster early warning and grading of set time are generated: grading the geological disaster monitoring and early warning according to the value of the geological landslide early warning index Q j and generating a geological disaster early warning tiff image layer;
S4, generating geological disaster early warning vector data of set time: and converting the geological disaster early warning tiff raster data of the set time into shp vector data.
2. The method for evaluating the risk of geological disasters according to claim 1, wherein in the step S1, original rainfall data at a future set time is obtained through a third party data platform, engineering files and data sources are created through a third party development library GDAL, the original rainfall data is read, original rainfall tiff images are created based on a GDAL component library, image projection conversion into a mercator-to-WGS 84 is realized through GDAL, the images of the rainfall WGS84 are reclassified according to regions, contour extraction is performed on the reclassified images, the contour is converted into an isosurface, and then a tiff image layer of the rainfall at the future set time is generated by cutting according to the isosurface.
3. The method for evaluating the risk of geological disasters according to claim 1, wherein in the step S2, the calculation formula of the regional geological landslide early warning index Q j is:
Q j = stratum lithology grading factor + seismic intensity grading factor · 5/8+ landform grading factor · 7/8+ terrain gradient factor/2 + rainfall · 5/8.
4. The method for evaluating the risk of geological disasters according to claim 2, wherein in the step S2, the stratum lithology grading coefficient quantization method is as follows:
the engineering geological rock group is loose soil, and the stratum lithology grading coefficient is defined as 0.177;
Engineering geological rock groups are invasive rock, and stratum lithology grading coefficients are defined as 0.052; the engineering geological rock group is blocky metamorphic rock, and the stratum lithology grading coefficient is defined as 0.061;
the engineering geological rock group is the sprayed rock, and the stratum lithology grading coefficient is defined as 0.077;
the engineering geological rock group is clastic rock, and the stratum lithology grading coefficient is defined as 0.219;
The engineering geological rock group is sheet or plate metamorphic rock, and the stratum lithology grading coefficient is defined as 0.199; the engineering geological rock group is carbonate rock, and the stratum lithology grading coefficient is defined as 0.091;
The engineering geological rock group is collapsible loess, and the stratum lithology grading coefficient is defined as 0.124.
The earthquake intensity quantification method comprises the following steps:
the seismic intensity is less than VI, and the seismic intensity grading coefficient is 0.06;
VI is less than or equal to seismic intensity and less than VII, and the seismic intensity grading coefficient is 0.121;
VII is less than or equal to seismic intensity and less than VIII, and the seismic intensity grading coefficient is 0.223;
VIII is less than or equal to seismic intensity and less than IX, and the seismic intensity grading coefficient is 0.277;
The seismic intensity is larger than or equal to IX, and the seismic intensity grading coefficient is 0.319.
The landform quantization method comprises the following steps:
the landform is plain, and the grading coefficient of the landform is 0.062;
The landform is hilly, and the grading coefficient of the landform is 0.085;
The landform is extremely high mountain, and the grading coefficient of the landform is 0.093;
The landform is mountain, and the grading coefficient of the landform is 0.106;
the landform is a plateau, and the grading coefficient of the landform is 0.135;
The landform is a low mountain, and the grading coefficient of the landform is 0.214;
the relief is a Zhongshan and the grading coefficient of the relief is 0.305.
The terrain gradient quantization method comprises the following steps:
the gradient is less than or equal to 15 degrees, and the gradient coefficient is 0.1;
15 DEG < gradient less than or equal to 25 DEG, and gradient coefficient is 0.219;
Gradient >40 °, gradient coefficient 0.244;
25 DEG < gradient less than or equal to 40 DEG, and gradient coefficient is 0.437.
5. The method for evaluating the risk of a geological disaster according to claim 1, wherein in the step S3, the geological disaster monitoring and early warning grade is classified into four grades of red, orange, yellow and green, and the red early warning indicates that the geological landslide early warning index is more than or equal to 0.195; the orange early warning indicates that the early warning index of the geological landslide is more than or equal to 0.193 and less than 0.195; yellow early warning means that the early warning index of the geological landslide is more than or equal to 0.177 and less than 0.193; the green early warning indicates that the geological landslide early warning index is less than 0.177.
6. The method for evaluating the risk of a geological disaster according to claim 1, wherein the step S4 comprises the steps of:
S41, binarizing the image;
S42, preprocessing the binary image;
s43, thinning: gradually stripping the points of the outline edge from the binary image pixel array to enable the binary image pixel array to be a skeleton pattern with a line width of only one pixel;
s44, tracking: converting the skeleton into a coordinate sequence of a vector graph;
S45, topological: and finding out the end points, nodes and isolated points of the line, and carrying out topology on the image.
7. The method for evaluating the risk of a geological disaster according to claim 6, wherein the step S43 comprises the steps of:
s431, determining a pixel set to be refined;
s432, removing the pixel element which is not a skeleton;
s433, repeating S432 until only skeleton pixel remains.
8. The method for evaluating the risk of a geological disaster according to claim 6, wherein the step S44 comprises the steps of:
S441, drawing a starting point along a search line and recording coordinates;
s442, tracking points in 8 directions of the starting point, if no point is tracked in 8 directions, finishing tracking the line, and returning to S441 to track the next line; if the tracking point is found, the coordinates of the tracking point are recorded;
s443, taking the point tracked in the step S422 as a new starting point, returning to the step S442, and continuously tracking 8 directions of the starting point; until connected into a boundary arc segment.
9. The method for evaluating the risk of a geological disaster according to claim 1, wherein the set time is 24 hours or 72 hours.
10. The method for evaluating the risk of a geological disaster according to any one of claims 1 to 9, further comprising the steps of:
And S5, issuing a geological disaster early warning map service for a set time, and comprehensively displaying the geological disaster risk evaluation vector data of the hydropower station.
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