Method for identifying high-risk avalanche trench

Abstract

The invention discloses a method for identifying high-risk avalanche trenches, which relates to the technical field of avalanche identification and comprises the following steps of: 1, calculating the snow collecting area of each trench; 2, the average gradient of the snow accumulation area of each groove and the area of the snow accumulation area of each groove are calculated, and the area ratio of the snow collection area to the snow accumulation area in each groove is obtained; and 3, when the area ratio is greater than or equal to a set ratio and the average gradient is greater than or equal to a set gradient, determining that the corresponding groove is a high-risk avalanche groove. According to the method, the avalanche groove is identified by combining the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area, the geomorphic main control factor of the groove type avalanche is directly considered, and the risk of the groove type avalanche in the to-be-identified drainage basin can be identified through high-precision remote sensing data; the target area is determined for subsequent installation of the avalanche monitoring instrument, and the technical problems that the landform master control indexes are not comprehensive, the identification difficulty is large, the cost is high and subsequent installation of the monitoring instrument is inconvenient in the existing identification method are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of avalanche identification, and in particular to a method for identifying a high-risk avalanche groove, which is particularly suitable for effectively identifying a high-risk avalanche groove in high-cold and high-altitude mountainous areas. Background Art

[0002] Avalanche is a snow disaster phenomenon in which the snow layer slides along the bottom or middle discontinuous layer under the disturbance of external factors and causes disasters. In recent years, under the background of climate change and human engineering activities, avalanche disasters have occurred frequently in mountainous areas and are showing an increasing trend. Among them, compared with slope avalanches, groove avalanches are the most widely developed, larger in scale and more disastrous. The early identification of this type of disaster has also become one of the urgent issues for disaster prevention and mitigation of important roads or major projects under planning.

[0003] The occurrence of trough avalanches often leads to major disasters such as road interruption, vehicle destruction and loss of life. Trough avalanches are highly unexpected and occur frequently in winter and spring, seriously restricting the development of the regional economy and the safety of vehicles and personnel. This type of avalanche often occurs repeatedly in the same trough, with significant repeatability. Therefore, in addition to the amount of snowfall, geomorphic factors have become an important basis for the identification of trough avalanches.

[0004] In order to better prevent avalanche disasters and reduce losses, it is necessary to conduct scientific and accurate early identification of avalanche disasters. At present, there are mainly two identification methods:

[0005] 1. The avalanche susceptibility evaluation system is constructed through many factors such as snow thickness, water content, thickness and type of deep frost, density, size and shape of snow crystals, snow layer structure, hardness, snow temperature and temperature gradient, slope, vegetation type and coverage, wind, snowfall and blowing snow, length of stable snow accumulation period, terrain cutting depth and other external factors (such as human and animal walking, rolling stones, etc.), and finally the high-prone avalanche grooves are identified according to the weighted scoring method. However, this method has technical problems such as difficulty in determining influencing factors and incompleteness of main control factors or their importance is weakened.

[0006] 2. Install radar, high-definition cameras and other monitoring instruments on avalanche troughs, or use SAR and other remote sensing images combined with avalanche relics to determine the most prone avalanche troughs. This method has high accuracy, but it is difficult to promote and apply in large areas, the remote sensing identification of avalanche relics is difficult, the cost is high, and the important main control factors are not fully considered.

[0007] In addition, it is found that trough avalanches often occur repeatedly in the same area, so the development of this type of avalanche is largely controlled by the topography. Practice has found that the channel of a trough avalanche has significant characteristics of snow collection area, snow accumulation area, circulation area and accumulation area, among which the snow collection area, circulation area and accumulation area are located at the top, middle and bottom of the slope respectively, and the snow accumulation area is located in the snow collection area. The snow collection area of ​​a trough avalanche is similar to the formation area of ​​the debris flow trough, and plays an important role in the formation of avalanches. At the same time, through the statistics of 47 avalanches in Yixiu La Mountain, Bukong La Mountain and Galung La Mountain, we found that the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area can well characterize the susceptibility of trough avalanches. Therefore, it is necessary to further consider the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area on the basis of the existing specifications and standards, and propose a new technology for the identification of high-risk avalanche grooves, so as to facilitate more accurate, convenient and efficient macroscopic identification of high-risk avalanche grooves. Summary of the invention

[0008] The purpose of the present invention is to overcome the above-mentioned problems existing in the prior art and provide a method for identifying high-risk avalanche grooves. The method combines the slope of the snow accumulation area and the area ratio of the snow collection area to the snow accumulation area to identify the avalanche groove. It not only directly considers the main geomorphic controlling factors of groove-type avalanches, but can also judge the degree of danger of groove-type avalanches in the identified basin from a macro perspective through high-precision remote sensing data, and determines the target area for the subsequent installation of avalanche monitoring instruments, thereby solving the technical problems of the existing identification methods, such as incomplete main geomorphic control indicators, great difficulty in identification, high cost and inconvenience in the subsequent installation of monitoring instruments.

[0009] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0010] A method for identifying a high-risk avalanche groove comprises the following steps:

[0011] Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data within the ridge lines on both sides of the road in the identified area;

[0012] Step S2: Find all the grooves and the groove heads in the ridge lines on both sides according to the high-precision DEM elevation data or multi-period remote sensing image data, determine the snow collection area and flow area of ​​each groove according to the groove head, and calculate the snow collection area area A of each groove ( Snow area ) ;

[0013] Step S3: select relatively flat areas with groove terrain in the snow collection area as snow accumulation areas, and calculate the average slope i of each groove snow accumulation area. ( Snow area ) and the snow accumulation area A of each groove ( Snow area ), and the area ratio A of the snow sinking area to the snow accumulation area in each groove is obtained ( Snow area ) / A ( Snow area ) ;

[0014] Step S4: When the area ratio of the snow sinking area to the snow accumulation area is A ( Snow area ) / A ( Snow area ) is greater than or equal to the set ratio, and the average slope i of the snow area ( Snow area ) When the slope is greater than or equal to the set slope, the corresponding groove is determined to be a high-risk avalanche groove.

[0015] In step S1, the high-precision DEM elevation data is the ASTER GDEM data obtained through the geospatial data cloud platform, or the DEM data obtained through the field survey drone; the multi-period remote sensing image data is the Sentinel data obtained through the Google Earth platform or the European Space Agency platform.

[0016] In step S1, the resolution of the high-precision DEM elevation data is 30m or 12.5m.

[0017] In step S2, the method for determining the head of the trench according to the high-precision DEM elevation data is as follows: first, the trench is segmented every 100m according to the high-precision DEM elevation data, the slope of each section from upstream to downstream is calculated, and then the sudden inflection point where the slope changes from small to large from upstream to downstream is found according to the slope, and the sudden inflection point is the head of the trench.

[0018] In step S2, the method for determining the head of the groove according to the multi-period remote sensing image data is as follows: the turning point from the upstream to the downstream of the main groove of the groove is found according to the multi-period remote sensing image data, and the turning point is the head of the groove.

[0019] In step S2, the snowfall area A ( Snow area ) The calculation method is as follows: first, the snow accumulation area is delineated in ArcGIS software according to multi-period remote sensing image data, and then the projection coordinates are assigned and calculated through the area calculation module of the field calculator in the attribute table.

[0020] In step S3, the snow accumulation area is an area in the snow collection area with a slope of 20° to 35° and a concave terrain.

[0021] In step S4, the ratio is set to 1.71, based on the 25% quantile of the statistical value of the avalanches that have occurred; the slope is set to 30°, based on the comprehensive statistics of the data of the avalanches that have occurred.

[0022] The advantages of adopting the present invention are:

[0023] 1. According to the characteristics of groove-type avalanches, which have significant snow collection areas, snow accumulation areas, circulation areas and accumulation areas, the present invention conducts in-depth research starting from two geomorphological indicators, namely the area ratio of the snow collection area to the snow accumulation area and the average slope of the snow accumulation area. It not only directly considers the main geomorphological controlling factors of groove-type avalanches, but can also judge the degree of danger of groove-type avalanches in the to-be-identified watershed from a macroscopic perspective through high-precision remote sensing data. It has the advantages of high judgment accuracy, relatively simple judgment process, low judgment cost, and convenience in determining the target area for the installation of subsequent avalanche monitoring instruments.

[0024] 2. The research objects and research scenarios of the present invention are relatively special. Since the occurrence of large-scale groove-type avalanche disasters in space is repetitive, it is particularly important to scientifically predict the avalanche grooves along important roads in high-cold and high-altitude engineering areas at this stage. Then, based on the characteristics of 47 groove-type avalanches in Yixiu La Mountain, Bukong La Mountain and Galung La Mountain, the geomorphic characteristics of the grooves on both sides of the hillsides along important roads were identified through research, the positions of the groove heads of the corresponding grooves were identified, and the snow accumulation area and snow sinking area of ​​the groove-type avalanche were further determined. The ratio index of the snow sinking area area and the snow accumulation area area used to characterize the volume of the avalanche supply source was calculated. The identification of high-risk avalanche grooves was carried out according to the identification index threshold obtained by statistics, which is conducive to more accurate and effective identification of groove-type avalanche disasters.

[0025] 3. The present invention sets the high-precision DEM elevation data to ASTER GDEM and other data that can be obtained through platforms such as the geospatial data cloud, and can also obtain DEM data with higher precision through field survey drones. Its advantages are that multi-channel data sources are more adaptable to more scenarios, especially open source DEM data is easy and fast to obtain and has low cost, which can overcome the problem of difficulty in field measurement in high-altitude unmanned areas.

[0026] 4. The method for determining the ditch head in the present invention can find the turning point from no ditch to the existing ditch from upstream to downstream according to the remote sensing image, or find the sudden turning point from small to large slope from upstream to downstream by analyzing the slope of the ditch. The two methods can determine the ditch head position respectively and make a comprehensive judgment, which ensures the reliability of the ditch head position determination and has strong operability.

[0027] 5. The present invention determines the threshold index of high risk as A ( Snow area ) / A ( Snow area ) ≥1.71, i ( Snow area )≥30°. In particular, the snow sinking area provides the necessary material conditions for the formation of avalanches, and the relatively flat groove area above the gully head is the snow accumulation area where avalanches start. The ratio of the snow sinking area to the snow accumulation area is derived from the statistical median of 47 avalanches in Yixiu La Mountain, Bukong La Mountain and Galung La Mountain, and the slope threshold is derived from industry standards and basic understanding. Its advantage is that it combines the slope indicators in existing research and industry standards, and focuses on the key control indicator A that can characterize the source of trough avalanche supply based on field cases. ( Snow area ) / A ( Snow area ) . BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flowchart of the present invention;

[0029] Figure 2 This is a statistical chart based on 47 avalanches on Yixiu La Mountain, Bukong La Mountain and Galung La Mountain. DETAILED DESCRIPTION

[0030] Example 1

[0031] like Figure 1 As shown, the present invention provides a method for identifying a high-risk avalanche groove, which comprises the following steps:

[0032] Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data within the ridge lines on both sides of the road in the identified area.

[0033] Specifically, the resolution of the above-mentioned high-precision DEM elevation data is 30m or 12.5m. The high-precision DEM elevation data can be ASTER GDEM data obtained through platforms such as the Geospatial Data Cloud, or higher-precision DEM data obtained through field survey drones; the multi-period remote sensing image data are Sentinel data obtained through the Google Earth platform or the European Space Agency platform.

[0034] Step S2: Find all the grooves and the groove heads in the ridge lines on both sides according to the high-precision DEM elevation data or multi-period remote sensing image data, determine the snow collection area and flow area of ​​each groove according to the groove head, and calculate the snow collection area area A of each groove ( Snow area ) .

[0035] Specifically, the snowfall area A ( Snow area )The calculation method is: first, the snowfall area is delineated in ArcGIS software based on multi-period remote sensing image data, and then the projection coordinates are assigned and the area calculation module of the field calculator in the attribute table is used for calculation. It should be noted that this calculation method is an existing conventional technical means and will not be described in detail.

[0036] Step S3: select relatively flat areas with groove terrain in the snow collection area as snow accumulation areas, and calculate the average slope i of each groove snow accumulation area. ( Snow area ) and the snow accumulation area A of each groove ( Snow area ) , and the area ratio A of the snow sinking area to the snow accumulation area in each groove is obtained ( Snow area ) / A ( Snow area ) .

[0037] Specifically, the above-mentioned snow accumulation area is an area in the snow collection area with a slope of 20° to 35° and a concave terrain.

[0038] Step S4: When the area ratio of the snow sinking area to the snow accumulation area is A ( Snow area ) / A ( Snow area ) is greater than or equal to the set ratio, and the average slope i of the snow area ( Snow area ) When the slope is greater than or equal to the set slope, the corresponding groove is judged to be a high-risk avalanche groove, indicating that the risk of groove-type avalanches occurring in the identified small watershed is high, and there is a high possibility of large-scale avalanche disasters occurring in the winter and spring seasons in the future.

[0039] Specifically, the above-mentioned set ratio is 1.71, which is based on the 25% quantile of the statistical values ​​of avalanches that have occurred in 47 places in Yixiula Mountain, Bukongla Mountain and Galungla Mountain; the above-mentioned set slope is 30°, which is based on the comprehensive statistics of data on avalanches that have occurred.

[0040] According to a preferred implementation of this embodiment, in step S2, the position of the groove head can be determined by two methods, respectively as follows:

[0041] The first method is to determine the position of the ditch head in the ditch according to the high-precision DEM elevation data. The specific method is: first divide the ditch into sections every 100m according to the high-precision DEM elevation data, calculate the slope of each section from upstream to downstream, and then find the sudden inflection point where the slope changes from small to large from upstream to downstream according to the slope. The sudden inflection point is the ditch head. It should be noted that the method of calculating the slope of each section is an existing conventional technical means and will not be repeated.

[0042] The second method is to determine the position of the trench head based on multi-period remote sensing image data. The specific method is to find the turning point from the upstream to the downstream main trench to the existing trench based on multi-period remote sensing image data. This turning point is the trench head.

[0043] It should be noted that, in practical applications, the position of the groove head can also be determined comprehensively based on the above two methods.

[0044] The identification method of the present invention is applicable to groove avalanches, i.e., grooves with obvious snow collection areas, snow accumulation areas, circulation areas and accumulation areas. The identification method comprehensively considers the ratio of the snow collection area to the snow accumulation area and the average slope of the snow accumulation area to identify whether the grooves developed on both sides of the road are high-risk avalanche grooves, with higher accuracy, simpler process, lower cost and stronger practicality.

[0045] Example 2

[0046] This embodiment verifies the identification method of embodiment 1, and the specific process is as follows:

[0047] S1. Taking the 1# and 2# avalanche disaster events along National Highway 219 as the central section, obtain DEM elevation data with a resolution of 12.5m covering the 1# and 2# avalanche grooves (from the ridges on both sides of Gongri Gabuqu to the river). In addition, obtain high-definition remote sensing images of the grooves through Google Earth.

[0048] S2, such as Figure 1 As shown in the figure, the position of the trough head in the trough was determined by remote sensing images, and the snow sinking area of ​​the 1# avalanche trough located on the right bank of Gongri Gabu Qu was calculated to be 54657m 2 , snow-covered area 31939m 2 The average slope of the snow accumulation area is 35.71°; the snow collection area of ​​the 2# avalanche trough on the right bank of Gongri Gabuqu is 156,590m 2 , snow-covered area 76214m 2 , with an average slope of 32.21°.

[0049] S3, such as Figure 2 As shown in the figure, the area ratio A of the snow sinking area to the snow accumulation area of ​​the 1# avalanche groove is calculated. ( Snow area ) / A ( Snow area ) The ratio of the snow sinking area to the snow accumulation area of ​​the 2# avalanche trough is 1.71. ( Snow area ) / A ( Snow area ) is 2.05.

[0050] S4. Based on the results of S2 and S3, the A of 1# avalanche trench ( Snow area ) / A ( Snow area ) is 1.71, which meets the condition of being greater than or equal to 1.71; the slope of the snow area is 35.71°, which meets the condition of being greater than or equal to 30°. ( Snow area ) / A ( Snow area ) is 2.05, which meets the condition of being greater than or equal to 1.71; the slope of the snow-covered area is 32.21°, which meets the condition of being greater than or equal to 30°, so 1# and 2# avalanche grooves are both determined to be high-risk avalanche grooves, which proves that the accuracy of the present invention is higher.

[0051] The above description is only a specific implementation mode of the present invention. Any feature disclosed in this specification, unless otherwise stated, can be replaced by other alternative features that are equivalent or have similar purposes; all the disclosed features, or all the steps in the methods or processes, except for mutually exclusive features and / or steps, can be combined in any way.

Claims

1. A method for identifying a high-risk avalanche trough, characterized in that The following steps are involved: Step S1, obtaining high-precision DEM elevation data and multi-period remote sensing image data within the ridge lines on both sides of the road in the identified area; Step S2: Find all the grooves and the groove heads in the ridge lines on both sides according to the high-precision DEM elevation data or multi-period remote sensing image data, determine the snow collection area and flow area of ​​each groove according to the groove head, and calculate the snow collection area area A of each groove ( Snow area ) ; Step S3: select relatively flat areas with groove terrain in the snow collection area as snow accumulation areas, and calculate the average slope i of each groove snow accumulation area. ( Snow area ) and the snow accumulation area A of each groove ( Snow area ) , and the area ratio A of the snow sinking area to the snow accumulation area in each groove is obtained ( Snow area ) / A ( Snow area ) ; Step S4: When the area ratio of the snow sinking area to the snow accumulation area is A ( Snow area ) / A ( Snow area ) is greater than or equal to the set ratio, and the average slope i of the snow area ( Snow area ) When the slope is greater than or equal to the set slope, the corresponding groove is determined to be a high-risk avalanche groove.

2. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S1, the high-precision DEM elevation data is the ASTER GDEM data obtained through the geospatial data cloud platform, or the DEM data obtained through the field survey drone; the multi-period remote sensing image data is the Sentinel data obtained through the Google Earth platform or the European Space Agency platform.

3. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S1, the resolution of the high-precision DEM elevation data is 30m or 12.5m.

4. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S2, the method for determining the head of the trench according to the high-precision DEM elevation data is as follows: first, the trench is segmented every 100m according to the high-precision DEM elevation data, the slope of each section from upstream to downstream is calculated, and then the sudden inflection point where the slope changes from small to large from upstream to downstream is found according to the slope, and the sudden inflection point is the head of the trench.

5. The method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S2, the method for determining the head of the groove according to the multi-period remote sensing image data is as follows: the turning point from the upstream to the downstream of the main groove of the groove is found according to the multi-period remote sensing image data, and the turning point is the head of the groove.

6. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S2, the snowfall area A ( Snow area ) The calculation method is as follows: first, the snow accumulation area is delineated in ArcGIS software according to multi-period remote sensing image data, and then the projection coordinates are assigned and calculated through the area calculation module of the field calculator in the attribute table.

7. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S3, the snow accumulation area is an area in the snow collection area with a slope of 20° to 35° and a concave terrain.

8. A method for identifying a high-risk avalanche groove according to claim 1, characterized in that: In step S4, the ratio is set to 1.71, based on the 25% quantile of the statistical value of the avalanches that have occurred; the slope is set to 30°, based on the comprehensive statistics of the data of the avalanches that have occurred.

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