Snow depth distribution simulation method and system combining terrain parameters and snow layer settlement deformation

Abstract

The application provides a snow depth distribution simulation method and system combining terrain parameters and snow layer settlement deformation, and belongs to the technical field of avalanche prevention. The application is based on a digital elevation model and regional snow data, and the initial snow depth distribution is corrected by an elevation gradient, and then a terrain constraint function is constructed by using key terrain factors such as slope, so that the spatial division and fine adjustment of the snow erosion area and the accumulation area on the slope are realized; finally, a snow layer compaction settlement model is introduced, the thickness attenuation and density evolution of the snow under different temperature and self-weight stress conditions are simulated with time, and a time-varying snow depth field more in line with the actual process is obtained. The application can quickly generate a rasterized snow depth distribution result with terrain control characteristics in the high mountain and valley area lacking intensive monitoring data, can effectively reflect the regulation and control effect of complex terrain and the characteristics of the snow itself on the spatial heterogeneity of the snow depth, and significantly improves the calculation precision of the snow depth distribution.

Description

Technical Field

[0001] This invention belongs to the field of avalanche prevention technology, specifically relating to a method and system for simulating snow depth distribution by combining terrain parameters with snow layer subsidence deformation. Background Technology

[0002] The spatial distribution characteristics of snow depth are key influencing factors in avalanche formation, snow load assessment, and the safety of high-altitude engineering facilities. In high-altitude canyon areas, complex terrain conditions, significant slope variations, and strong spatial differences in meteorological elements result in a highly heterogeneous snow layer thickness. Detailed spatial simulation of slope snow depth is a crucial foundation for avalanche hazard analysis, disaster prevention design of power transmission lines, and operation and maintenance of highway and hydropower projects.

[0003] Currently, the spatial distribution of snow depth mainly relies on snow depth interpolation methods from field observation stations. Limited snow depth data obtained from meteorological stations and manual observation points are used for two-dimensional spatial interpolation through methods such as inverse distance weighting and ordinary kriging. These methods estimate regional snow depth based on only a small number of discrete points and do not incorporate control factors such as topographic relief and slope, making it difficult to reflect the true characteristics of snow cover distribution on slopes. Furthermore, the density and thickness of fresh snow changing significantly over time from its initial fall to the formation of a stable snow layer. In areas with dramatic high-altitude topography, interpolation methods relying solely on a small number of monitoring points are insufficient to obtain reliable snow depth distributions.

[0004] More importantly, most high-altitude canyon areas lack a comprehensive snow cover monitoring system. The density of meteorological stations is low, making it difficult to obtain key snow cover parameters such as snow depth and density; in some engineering corridors, snow cover monitoring equipment is completely absent. Due to factors such as poor transportation conditions, high altitude, and harsh field environments, large-scale deployment of monitoring equipment such as laser rangefinders, ultrasonic snow depth meters, and snow weather towers requires substantial financial investment, has a long construction period, and is difficult to maintain, making snow depth estimation methods relying on observational data impractical in high-altitude areas.

[0005] Existing technologies include some relatively complex snow layer models and three-dimensional snow cover simulation systems that can simulate the evolution of snow layer structure and snow redistribution under the influence of multiple meteorological factors. However, these models rely on long-term and complete meteorological driving data, have numerous parameters and complex calibration, and require high computational resources, making them difficult to deploy and promote in engineering practice.

[0006] Therefore, it is necessary to provide a method and system for simulating snow depth distribution by combining topographic parameters and snow layer subsidence deformation to solve the above problems. Summary of the Invention

[0007] This invention provides a method and system for simulating snow depth distribution by combining topographic parameters and snow layer settlement deformation. It can make full use of the topographic information in the digital elevation model to automatically identify potential avalanche hazard areas at small scales in large mountainous areas, providing a reliable basis for avalanche dynamics simulation, risk assessment and disaster prevention engineering layout, thereby effectively solving at least one of the technical problems involved in the background art.

[0008] To solve the above-mentioned technical problems, the present invention is implemented as follows:

[0009] A method for simulating snow depth distribution by combining topographic parameters and snow layer subsidence deformation includes the following steps:

[0010] Step S1: Obtain the digital elevation model of the target area, and preprocess the digital elevation model to obtain continuous and complete terrain data;

[0011] Step S2: Calculate the slope of the target area based on the terrain data;

[0012] Step S3: Based on the empirical value of snow depth variation with elevation in the target area, set the unit elevation snow depth variation rate, select a benchmark point and obtain the elevation and snow depth of the benchmark point, and calculate the elevation correction snow depth of the target location based on the elevation difference of any target location in the target area relative to the benchmark point, combined with the unit elevation snow depth variation rate.

[0013] Step S4: Construct a terrain correction function to characterize the stability of snow cover under different slope conditions, and further correct the elevation-corrected snow depth to obtain the terrain-corrected snow depth.

[0014] Step S5: Using the terrain-corrected snow depth as the initial snow depth, construct a snow layer settlement model based on the snow layer compaction and settlement theory to simulate the change of snow depth over time and obtain the snow depth after settlement.

[0015] Step S6: Traverse all locations within the target area and output the time-varying snow depth field after the target area has settled.

[0016] As a preferred improvement, in step S1, the digital elevation model is obtained from UAV aerial photography or high-precision remote sensing image interpretation.

[0017] As a preferred improvement, in step S1, the preprocessing process is performed using ArcGIS, and the preprocessing process includes:

[0018] (1) Use bilinear interpolation to fill the holes in a very small number of missing rasters;

[0019] (2) Median filtering correction is applied to isolated outliers;

[0020] (3) Perform boundary trimming to make it consistent with the snow depth distribution simulation area.

[0021] As a preferred improvement, the slope of the target area is obtained by calculating the first derivative of the elevation information of the target area.

[0022] As a preferred improvement, the slope is calculated as follows:

[0023] ;

[0024] In the formula, z represents the slope; z represents the elevation. x The horizontal coordinates are in the east-west direction; y The coordinates are north-south horizontal coordinates; / and / These represent the elevation change rates in the east-west and north-south directions, respectively.

[0025] As a preferred improvement, the initial snow depth at the target location Represented as:

[0026]

[0027] In the formula, The reference snow depth indicates the reference point; The reference elevation represents the reference point. This represents the rate of change of snow depth per unit elevation. Indicates the elevation of the target location.

[0028] As a preferred improvement, the terrain correction function Represented as:

[0029]

[0030] In the formula, Indicates the critical slope; , Represents the empirical coefficient;

[0031] Terrain-corrected snow depth Represented as:

[0032]

[0033] As a preferred improvement, the snow cover settlement model is expressed as:

[0034]

[0035]

[0036] In the formula, express The density of the snow layer after constant settling; This indicates the normal stress of the overlying snow. , Indicates the density of new snow; Represents gravitational acceleration; This represents the settlement deformation coefficient, which is related to the snow density. and temperature related; express The snow depth changes over time after the snow settles.

[0037] A system for performing the above-described method for simulating snow depth distribution by combining terrain parameters with snow cover subsidence deformation, comprising:

[0038] The terrain data acquisition module acquires a digital elevation model of the target area and preprocesses the digital elevation model to obtain continuous and complete terrain data.

[0039] The slope calculation module calculates the slope of the target area based on the terrain data;

[0040] The elevation correction module sets the unit elevation snow depth change rate based on the empirical value of snow depth variation with elevation in the target area, selects a benchmark point and obtains the elevation and snow depth of the benchmark point, and calculates the elevation correction snow depth of the target location based on the elevation difference of any target location in the target area relative to the benchmark point, combined with the unit elevation snow depth change rate.

[0041] The terrain correction module constructs a terrain correction function to characterize the stability of snow cover under different slope conditions, and further corrects the elevation-corrected snow depth to obtain the terrain-corrected snow depth.

[0042] The settlement correction module uses the terrain-corrected snow depth as the initial snow depth, constructs a snow layer settlement model based on snow layer compaction and settlement theory, simulates the relationship between snow depth and time, and obtains the snow depth after settlement.

[0043] The output module iterates through all locations within the target area and outputs the time-varying snow depth field after the target area has settled.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) Significantly reduces dependence on monitoring equipment and measured data: Only high-precision DEM and a small number of regional snow depth parameters are needed to complete the simulation, which is suitable for high mountain and canyon areas with few monitoring stations and high deployment costs;

[0046] (2) Fully reflect the control effect of topography on snow depth distribution: By combining elevation correction and local topography correction, it is possible to distinguish between erosion areas and deposition areas, and obtain a more realistic gridded snow depth distribution;

[0047] (3) The snow layer settlement evolution process can be considered: introduce a snow layer settlement model to simulate the evolution of snow depth and density over time after snowfall, and provide support for the avalanche risk assessment and structural cumulative load analysis at different times;

[0048] (4) The method is simple, efficient and easy to apply in engineering: The algorithm has a clear structure and can be embedded in existing GIS platforms or independent software. It is suitable for large-scale snow depth distribution simulation in high-altitude engineering projects, providing reliable data support for avalanche risk analysis, snow load assessment and disaster prevention design of engineering facilities in high-altitude and cold regions. It has good engineering promotion value. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein:

[0050] Figure 1 A flowchart of the snow depth distribution simulation method combining terrain parameters and snow layer subsidence deformation provided by the present invention;

[0051] Figure 2 The above are the simulation results of snow depth distribution in the target area after elevation correction in Example 1;

[0052] Figure 3 The simulation results of snow depth distribution in the target area after terrain correction in Example 1;

[0053] Figure 4 The results are simulations of snow depth distribution after snow compaction and settlement in the target area in Example 1. Detailed Implementation

[0054] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] like Figure 1 As shown, this embodiment provides a method for simulating snow depth distribution by combining terrain parameters and snow layer subsidence deformation, including the following steps:

[0056] Step S1: Obtain the digital elevation model of the target area, and preprocess the digital elevation model to obtain continuous and complete terrain data.

[0057] The digital elevation model (DEM) is obtained through on-site UAV aerial photography or interpretation of high-precision remote sensing images, with a resolution of 1-5m, and the appropriate scale is selected according to engineering requirements. The digital elevation model (DEM) includes an elevation matrix and its spatial reference information.

[0058] The preprocessing process includes:

[0059] (1) Use bilinear interpolation to fill the holes in a very small number of missing rasters;

[0060] (2) Median filtering correction is applied to isolated outliers;

[0061] (3) Perform boundary trimming to make it consistent with the subsequent snow depth simulation area.

[0062] The preprocessing process is completed using ArcGIS, which ensures the stability and continuity of subsequent terrain analysis.

[0063] Step S2: Calculate the slope of the target area based on the terrain data.

[0064] Slope S, used to characterize the slope angle, is a major controlling factor for snow erosion, accumulation, and slippage. It is obtained by calculating the first derivative from the elevation information of the target area; the specific calculation process is as follows:

[0065] ;

[0066] In the formula, z is the elevation; x The horizontal coordinates are in the east-west direction; y The coordinates are north-south horizontal coordinates; / and / These represent the elevation change rates of the DEM in the east-west and north-south directions, respectively, used to calculate the slope angle.

[0067] Step S3: Based on the empirical value of snow depth variation with elevation within the target area, set the unit elevation snow depth variation rate, select a benchmark point and obtain the benchmark point's elevation and snow depth, and calculate the elevation correction snow depth of the target location based on the elevation difference between any target location within the target area and the benchmark point, combined with the unit elevation snow depth variation rate.

[0068] Initial snow depth at the target location Represented as:

[0069]

[0070] In the formula, The reference snow depth indicates the reference point; The reference elevation represents the reference point. This represents the rate of change of snow depth per unit elevation. Indicates the elevation of the target location.

[0071] Step S4: Construct a terrain correction function to characterize the stability of snow cover under different slope conditions, and further correct the elevation-corrected snow depth to obtain the terrain-corrected snow depth.

[0072] The terrain correction function effectively reflects the stability characteristics of snow accumulation under different slope conditions by suppressing slip erosion in areas with gentle slopes and inhibiting snow accumulation in areas with steep slopes. Represented as:

[0073]

[0074] In the formula, The critical slope is represented by a value of 28° in this embodiment. When the slope is less than the critical slope, the slope is gentle and snow is easy to accumulate. When the slope is greater than the critical slope, the snow is easy to slide and terrain correction is required. , The values ​​represent empirical coefficients, which are 0.291 and 0.202 in this embodiment. In other embodiments, they can be adjusted based on historical snow cover monitoring data.

[0075] Terrain-corrected snow depth Represented as:

[0076]

[0077] Step S5: Using the terrain-corrected snow depth as the initial snow depth, construct a snow layer settlement model based on the snow layer compaction and settlement theory to simulate the change of snow depth over time and obtain the snow depth after settlement.

[0078] The snow layer settlement model simulates the evolution of snow depth and density over time based on the theory of snow layer compaction and settlement. By calculating the increase of snow layer density over time and the decrease of snow depth over time, the snow layer density and snow depth at different times can be obtained.

[0079] The snow layer settlement model is represented as follows:

[0080]

[0081]

[0082] In the formula, express The density of the snow layer after constant settling; This indicates the normal stress of the overlying snow. , This represents the density of fresh snow, which is taken as 120 kg / m³ in this embodiment. Represents gravitational acceleration; This represents the settlement deformation coefficient, which is related to the snow density. and temperature related; express The snow depth changes over time after the snow settles.

[0083] The settlement deformation coefficient Obtained from experimental fitting, and expressed as:

[0084]

[0085] In the formula, This represents the initial value of the settlement deformation coefficient; This indicates the temperature of the snow layer.

[0086] Step S6: Traverse all locations within the target area and output the time-varying snow depth field after the target area has settled.

[0087] After the above elevation, topography and settlement corrections, the output is a rasterized snow depth distribution result including the initial snow depth, the elevation-corrected snow depth, the topography-corrected snow depth and the snow depth after settlement.

[0088] This embodiment also provides a system for performing the above-described method for simulating snow depth distribution by combining terrain parameters and snow layer subsidence deformation, comprising:

[0089] The terrain data acquisition module acquires a digital elevation model of the target area and preprocesses the digital elevation model to obtain continuous and complete terrain data.

[0090] The slope calculation module calculates the slope of the target area based on the terrain data;

[0091] The elevation correction module sets the unit elevation snow depth change rate based on the empirical value of snow depth variation with elevation in the target area, selects a benchmark point and obtains the elevation and snow depth of the benchmark point, and calculates the elevation correction snow depth of the target location based on the elevation difference of any target location in the target area relative to the benchmark point, combined with the unit elevation snow depth change rate.

[0092] The terrain correction module constructs a terrain correction function to characterize the stability of snow cover under different slope conditions, and further corrects the elevation-corrected snow depth to obtain the terrain-corrected snow depth.

[0093] The settlement correction module uses the terrain-corrected snow depth as the initial snow depth, constructs a snow layer settlement model based on snow layer compaction and settlement theory, simulates the relationship between snow depth and time, and obtains the snow depth after settlement.

[0094] The output module iterates through all locations within the target area and outputs the time-varying snow depth field after the target area has settled.

[0095] Example 1

[0096] This embodiment uses a snow depth distribution simulation method combining terrain parameters and snow layer subsidence deformation, provided by the present invention, to simulate the snow depth distribution in a target area. A monitoring station is set up at an altitude of 1300m in the target area, and this monitoring station is used as the reference point. Therefore, the reference elevation is 1300m above sea level, and the reference snow depth is 0.5m. Field monitoring data shows that the snow depth variation rate per unit elevation in this area is 0.05m / 100m.

[0097] The temperature of the target area is -5℃, and the initial value of the settlement deformation coefficient is taken as: Pa·s is used to calculate the snow depth and density distribution at times such as t = 24 h, 48 h, and 72 h by hourly integration.

[0098] After elevation, topographic, and settlement corrections, the output is a rasterized snow depth distribution containing the initial snow depth, elevation-corrected snow depth, topographic-corrected snow depth, and snow depth after settlement, as shown below. Figures 2-4 As shown.

[0099] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit of the present invention, and all of these forms are within the protection scope of the present invention.

Claims

1. A method for simulating snow depth distribution by combining topographic parameters and snow layer subsidence deformation, characterized in that, Includes the following steps: Step S1: Obtain the digital elevation model of the target area, and preprocess the digital elevation model to obtain continuous and complete terrain data; Step S2: Calculate the slope of the target area based on the terrain data; Step S3: Based on the empirical value of snow depth variation with elevation in the target area, set the unit elevation snow depth variation rate, select a benchmark point and obtain the elevation and snow depth of the benchmark point, and calculate the elevation correction snow depth of the target location based on the elevation difference of any target location in the target area relative to the benchmark point, combined with the unit elevation snow depth variation rate. Step S4: Construct a terrain correction function to characterize the stability of snow cover under different slope conditions, and further correct the elevation-corrected snow depth to obtain the terrain-corrected snow depth. Step S5: Using the terrain-corrected snow depth as the initial snow depth, construct a snow layer settlement model based on the snow layer compaction and settlement theory to simulate the change of snow depth over time and obtain the snow depth after settlement. Step S6: Traverse all locations within the target area and output the time-varying snow depth field after the target area has settled. Terrain correction function Represented as: In the formula, Indicates the critical slope; , Represents the empirical coefficient; Indicates slope; Terrain-corrected snow depth Represented as: ； In the formula, Indicates the initial snow depth at the target location.

2. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 1, characterized in that, In step S1, the digital elevation model is obtained from UAV aerial photography or high-precision remote sensing image interpretation.

3. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 1, characterized in that, In step S1, the preprocessing process is completed using ArcGIS, and the preprocessing process includes: (1) Use bilinear interpolation to fill the holes in a very small number of missing rasters; (2) Median filtering correction is applied to isolated outliers; (3) Perform boundary trimming to make it consistent with the snow depth distribution simulation area.

4. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 1, characterized in that, The slope of the target area is obtained by calculating the first derivative of the elevation information of the target area.

5. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 4, characterized in that, The slope is calculated as follows: ； In the formula, z is the elevation of the target location; x The horizontal coordinates are in the east-west direction; y The coordinates are north-south horizontal coordinates; / and / These represent the elevation change rates in the east-west and north-south directions, respectively.

6. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 5, characterized in that, Initial snow depth at the target location Represented as: In the formula, The reference snow depth indicates the reference point; The reference elevation indicates the reference point; This represents the rate of change of snow depth per unit elevation.

7. The snow depth distribution simulation method combining topographic parameters and snow layer subsidence deformation according to claim 1, characterized in that, The snow layer settlement model is represented as follows: In the formula, express The density of the snow layer after constant settling; This indicates the normal stress of the overlying snow. , Indicates the density of new snow; Represents gravitational acceleration; This represents the settlement deformation coefficient, which is related to the snow density. and temperature related; express The snow depth changes over time after the snow settles.

8. A system for performing the snow depth distribution simulation method combining terrain parameters and snow layer subsidence deformation as described in any one of claims 1-7, characterized in that, include: The terrain data acquisition module acquires a digital elevation model of the target area and preprocesses the digital elevation model to obtain continuous and complete terrain data. The slope calculation module calculates the slope of the target area based on the terrain data; The elevation correction module sets the unit elevation snow depth change rate based on the empirical value of snow depth variation with elevation in the target area, selects a benchmark point and obtains the elevation and snow depth of the benchmark point, and calculates the elevation correction snow depth of the target location based on the elevation difference of any target location in the target area relative to the benchmark point, combined with the unit elevation snow depth change rate. The terrain correction module constructs a terrain correction function to characterize the stability of snow cover under different slope conditions, and further corrects the elevation-corrected snow depth to obtain the terrain-corrected snow depth. The settlement correction module uses the terrain-corrected snow depth as the initial snow depth, constructs a snow layer settlement model based on snow layer compaction and settlement theory, simulates the relationship between snow depth and time, and obtains the snow depth after settlement. The output module iterates through all locations within the target area and outputs the time-varying snow depth field after the target area has settled.

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