Debris flow scale estimation method

Abstract

The invention discloses a debris flow scale estimation method. The method comprises the following steps: acquiring related information of a drainage basin to be estimated; printing to obtain a 3D printing model of the drainage basin to be estimated; a blank slope body on the 3D printing model is scanned to obtain a three-dimensional point cloud, and the three-dimensional point cloud is converted into an original terrain where no material source is laid; laying a corresponding soil body on the 3D printing model to simulate an object source condition; early-stage precipitation is conducted on the 3D printing model after the corresponding soil body is laid, and the precipitation amount is recorded till the natural water content is achieved; a real precipitation process is simulated on the 3D printing model; the total amount of solid substances of the simulated debris flow is obtained, and a DEM after the disaster is obtained through scanning; and amplifying the total amount of debris flow solid substances according to the cubic of x to serve as a lower limit value, subtracting the DEM after the disaster from the DEM before the disaster according to the cubic of x to serve as an upper limit value, and obtaining an estimated debris flow scale. According to the method, the whole process from rainfall to debris flow rushing out is simulated on the terrain closer to the reality, and the accuracy of the estimation result is improved.

Description

Technical Field

[0001] The invention relates to a debris flow scale estimation method, in particular to a debris flow scale estimation method based on a 3D printing model test and taking into account the amount of material source, and belongs to the field of geological engineering. Background Art

[0002] The current rain-flood method for estimating the scale of debris flows does not take into account the material source, and only multiplies the clean water flow by the blockage coefficient representing the terrain and the sediment correction coefficient representing the bulk density of the debris flow (T / CAGHP 006-2018 Specifications for Engineering Investigation of Debris Flow Disaster Prevention). However, the material source is the basis of debris flow activity and is crucial to the occurrence of debris flow disasters. The addition of material sources makes debris flows less frequent than floods and more difficult to predict; they are much larger in scale than floods and more likely to cause disasters (deHaas et al., 2018; Johnson et al., 1991).

[0003] Based on the debris flow disaster site and remote sensing interpretation, some first use different methods to estimate the source volume, i.e., the source quantity (Cao et al., 2021), and then qualitatively assess that channels with more source quantity are likely to experience larger debris flows (Liang et al., 2023). Based on field monitoring work; (Tang et al., 2020) and others in Chalk Cliffs, Colorado based on the monitoring of the debris flow formation and movement process, (Imaizumi et al., 2017; Jakob et al., 2005) based on field investigations, studied the impact of different sediment supply conditions on the scale of debris flows.

[0004] However, due to objective conditions, rainfall is variable and sediment supply conditions are also constantly changing, making it difficult to independently obtain the impact of the amount of material on the scale. In terms of numerical calculations, the study of rainfall runoff, flood erosion and entrainment of sediments, and the landslide initiation and erosion entrainment models of debris flow formation and movement belong to different mature systems (Trujillo-Vela et al., 2022). Openlisem attempts to establish a numerical model of the entire process from rainfall to debris flow, but the sensitivity of the material source parameters produced by the model to the scale of debris flow comes from the coupling results of the existing rainfall runoff process and erosion entrainment mathematical model (Baartman et al., 2013). The model was not established and corrected based on monitoring or experiments of the entire process of rainfall-runoff-debris flow, and therefore lacks attention to some key processes of scale formation.

[0005] As observed in existing experiments, the unstable soil belongs to the landslide and erosion entrainment system, and the surface and interior of the unstable soil are running the rainfall-runoff / seepage system smoothly. In the flume debris flow initiation test; (Wang et al., 2017) and others tested the debris flow initiation amount of different ditch source soil compositions; (Berti and Simoni, 2005; de Haase et al., 2015) and others tested the debris flow outflow under different ditch bed soil thicknesses. However, due to the geometric shape of the flume, it is difficult to study the entire process from rainfall runoff generation and convergence to debris flow initiation and outflow. Summary of the invention

[0006] The purpose of the present invention is to overcome the above-mentioned problems existing in the prior art and provide a debris flow scale estimation method based on 3D printing model test taking into account the amount of material source. The present invention estimates the debris flow scale by simulating the entire process from precipitation to debris flow rushing out, simulating the entire process from precipitation to debris flow rushing out on a terrain closer to the real one, and improving the accuracy of the estimation result.

[0007] To achieve the above purpose, the technical solution adopted by the present invention is as follows: A method for estimating the scale of a debris flow, characterized in that it comprises the following steps: a. Obtain the topographic DEM, material source area, and material source thickness of the watershed to be estimated, determine the particle size distribution, density, and natural water content of the material source, and obtain the precipitation intensity of different frequencies in the watershed to be estimated i and time t ; b. Determine the scale ratio 1: x , according to the scale ratio and the terrain DEM of the watershed to be estimated, a 3D printing model of the watershed to be estimated is obtained; c. Scan the blank slope on the 3D printed model to obtain a three-dimensional point cloud, which is converted into the original terrain without paved sources; d. According to the source area and source thickness of the watershed to be estimated, the model is reduced in a ratio of 1:x, and the corresponding soil is laid on the 3D printed model according to the reduced area and thickness to simulate the source situation; e. Carry out preliminary precipitation on the 3D printed model after laying the corresponding soil and record the precipitation to the natural moisture content; f. Scan the soil with the pre-set moisture content to obtain the point cloud, i.e., the DEM before the disaster, and subtract it from the three-dimensional point cloud in step c to obtain the source distribution of the material to be laid, compare it with the actual situation of the watershed to be estimated, adjust the source distribution, and scan again until the laying situation is consistent with the actual situation; g. According to the designed precipitation intensity and precipitation time, simulate the real precipitation process on the 3D printed model; h. During precipitation, the Froude number is calculated by the precipitation velocity. If the Froude number is in the range of 0.5-7.6, it is judged to be similar to the watershed to be estimated; i. After the precipitation stops, wait for the solid material to be transported, obtain the total amount of simulated debris flow solid material, and perform post-disaster three-dimensional laser scanning on the 3D printed model to obtain the post-disaster DEM; j. The total amount of solid matter in the debris flow is magnified by the cube of x as the lower limit, and the DEM after the disaster is subtracted from the DEM before the disaster by the cube of x as the upper limit to obtain the estimated scale of the debris flow.

[0008] In the step a, a drone equipped with a laser radar is used to take aerial photos of the entire watershed, and the drone supporting software is used for post-processing to obtain a high-precision watershed terrain DEM; or a DEM produced by the French Pleiades satellite with an accuracy of 2m is directly purchased.

[0009] In step a, the source area is determined by remote sensing interpretation of aerial photography or satellite images; the source thickness is determined by on-site investigation or use of geological radar.

[0010] In step a, the particle size distribution, density and natural water content of the source of the watershed to be estimated are investigated on site; the precipitation intensity of different frequencies in the area is obtained by querying i and time t .

[0011] In step f, the source distribution includes source quantity, location and thickness.

[0012] In step g, the precipitation intensity and precipitation time are scaled down by x^(1 / 2) times of the actual precipitation intensity and precipitation time of the basin to be estimated.

[0013] In the step h, the precipitation process is recorded by video, and a pigment is used as a tracer to measure the precipitation velocity at the mountain pass, and the Froude number is calculated based on the precipitation velocity.

[0014] In the step h, if the calculated Froude number is not in the range, the test is repeated until the obtained Froude number is in the range of 0.5-7.6.

[0015] In step j, the erosion amount and erosion distribution information of the debris flow are obtained according to the estimated debris flow scale, and the image range of the debris flow is outlined based on the erosion distribution information to obtain the area that may be affected by the debris flow.

[0016] The advantages of adopting the present invention are: 1. This invention proposes a new technical system to simulate the complex physical process in nature to solve the complex equation "f (topography, water source, material source) = debris flow scale". As a powerful supplement to theoretical derivation and numerical simulation, it solves the problem that the existing methods cannot independently consider the relationship between material source and debris flow scale. The debris flow scale is estimated through the whole process test, the estimation method is simpler, and the results are real and effective.

[0017] 2. The present invention simulates many processes that are not completed continuously in traditional flume tests, such as rainfall runoff, seepage convergence, landslide instability initiation, liquefaction flow, erosion entrainment and accumulation, in one test process, which has a high similarity with the actual events, and the obtained simulation results are closer to the watershed to be estimated.

[0018] 3. The present invention fully and independently considers the influence of material sources on the scale of debris flow. It is a good experimental method for estimating the scale of debris flow, the scale of glacial lake outburst and the impact distance, the interaction of multiphase flows on terrain such as the encounter and accumulation of debris flow and flood, which cannot be achieved by current field monitoring, simulation and experimental technologies.

[0019] 4. Compared with the traditional flume test, the present invention is more complete: because it is combined with a 3D printed model, it can simulate the entire process from precipitation to mudslide on a terrain that is closer to the real thing.

[0020] 5. Compared with numerical simulation test, the present invention is faster and more reasonable: the present invention simulates the terrain of 6.1km2 with a scale of 1:2000 and an accuracy of 0.4m, and one test process only takes 10 minutes. However, the MPM methods such as massflow, ravaflow, PFC, and openlisem require computing stations for calculation, and the time consumed is measured in days and months. DETAILED DESCRIPTION

[0021] Example 1 A method for estimating the scale of a debris flow comprises the following steps: a. Obtain the topographic DEM, material source area, and material source thickness of the watershed to be estimated, determine the particle size distribution, density, and natural moisture content of the material source, and query the precipitation intensity of different frequencies in the watershed to be estimated i and time t ; b. Determine the scale ratio 1: x , according to the scale ratio and the terrain DEM of the watershed to be estimated, a 3D printing model of the watershed to be estimated is obtained; c. Scan the blank slope on the 3D printed model to obtain a three-dimensional point cloud, which is converted into the original terrain without paved sources; d. According to the source area and source thickness of the watershed to be estimated, the model is reduced in a ratio of 1:x, and the corresponding soil is laid on the 3D printed model according to the reduced area and thickness to simulate the source situation; e. Carry out preliminary precipitation on the 3D printed model after laying the corresponding soil and record the precipitation to the natural moisture content; f. Scan the soil with the pre-set moisture content to obtain the point cloud, i.e., the DEM before the disaster, and subtract it from the three-dimensional point cloud in step c to obtain the source distribution of the material to be laid, compare it with the actual situation of the watershed to be estimated, adjust the source distribution, and scan again until the laying situation is consistent with the actual situation; g. According to the designed precipitation intensity and precipitation time, simulate the real precipitation process on the 3D printed model; h. During precipitation, the Froude number is calculated by the precipitation velocity. If the Froude number is in the range of 0.5-7.6, it is judged to be similar to the watershed to be estimated; i. After the precipitation stops, wait for the solid material to be transported, obtain the total amount of simulated debris flow solid material, and perform post-disaster three-dimensional laser scanning on the 3D printed model to obtain the post-disaster DEM; j. The total amount of solid matter in the debris flow is magnified by the cube of x as the lower limit, and the DEM after the disaster is subtracted from the DEM before the disaster by the cube of x as the upper limit to obtain the estimated scale of the debris flow.

[0022] In the step a, a drone equipped with a laser radar is used to take aerial photos of the entire watershed, and the drone supporting software is used for post-processing to obtain a high-precision watershed terrain DEM; or a DEM produced by the French Pleiades satellite with an accuracy of 2m is directly purchased.

[0023] In step a, the source area is determined by remote sensing interpretation of aerial photography or satellite images; the source thickness is determined by on-site investigation or use of geological radar.

[0024] In step a, the particle size distribution, density and natural water content of the source of the watershed to be estimated are investigated on site; the precipitation intensity of different frequencies in the area is obtained by querying i and time t .

[0025] In step f, the source distribution includes source quantity, location and thickness.

[0026] In step g, the precipitation intensity and precipitation time are scaled down by x^(1 / 2) times of the actual precipitation intensity and precipitation time of the basin to be estimated.

[0027] In the step h, the precipitation process is recorded by video, and a pigment is used as a tracer to measure the precipitation velocity at the mountain pass, and the Froude number is calculated based on the precipitation velocity.

[0028] In the step h, if the calculated Froude number is not in the range, the test is repeated until the obtained Froude number is in the range of 0.5-7.6.

[0029] In step j, the scale of the debris flow ≈ the total amount of solid matter in the debris flow. According to the estimated scale of the debris flow, the erosion amount and erosion distribution information of the debris flow are obtained. Based on the erosion distribution information, the image range of the debris flow is outlined to obtain the area that may be affected by the debris flow.

[0030] Example 2 This embodiment illustrates the experimental process involved in the method of the present invention.

[0031] The test is as follows: (1) 3D printed scaled terrain model, 2688*921*1226mm, reduced by x times, made of gum.

[0032] (2) Soil simulating the source.

[0033] (3) A system for simulating precipitation; including sprinkler heads, pressure controllers, water pumps and racks for fixing sprinkler heads.

[0034] (4) The instrument used to obtain the total amount of punch-out is a Trimble SX12 3D scanner with a ranging noise of 1.5 mm and a point spacing of 6.25 mm.

[0035] (5) Test parameters: The parameters of the model design include soil particle diameter D, soil volume V s , initial soil moisture content ω, precipitation intensity i, precipitation time t, basin area F, gradient b, gravity acceleration g, the target parameters are the peak flow velocity μ at the exit, the maximum flow depth H of the debris flow at the exit, the peak flow rate Q at the exit, the debris flow time T, and the total amount V all , k is the coefficient of the pentagonal generalized flow process.

[0036] According to the test conditions, the scale ratio of the watershed model is 1:x. Considering that the gravitational acceleration is constant, the time scale is x^(1 / 2), and the water content ω and gradient b are also constant.

[0037] The estimation method of the present invention was used in the analysis and research of the debris flow in Chenghuangmiaogou, Xiaojin County, Sichuan Province, to estimate the maximum possible debris flow scale in the future and guide the house construction and farmland planning in the area.

Claims

1. A method for estimating the scale of debris flow, characterized in that: The steps include: a. Obtain the topographic DEM, material source area, and material source thickness of the watershed to be estimated, determine the particle size distribution, density, and natural water content of the material source, and obtain the precipitation intensity of different frequencies in the watershed to be estimated i and time t ; b. Determine the scale ratio 1: x , according to the scale ratio and the terrain DEM of the watershed to be estimated, a 3D printing model of the watershed to be estimated is obtained; c. Scan the blank slope on the 3D printed model to obtain a three-dimensional point cloud, which is converted into the original terrain without paved sources; d. According to the source area and source thickness of the watershed to be estimated, the model is reduced in a ratio of 1:x, and the corresponding soil is laid on the 3D printed model according to the reduced area and thickness to simulate the source situation; e. Carry out preliminary precipitation on the 3D printed model after laying the corresponding soil and record the precipitation to the natural moisture content; f. Scan the soil with the pre-set moisture content to obtain the point cloud, i.e., the DEM before the disaster, and subtract it from the three-dimensional point cloud in step c to obtain the source distribution of the material to be laid, compare it with the actual situation of the watershed to be estimated, adjust the source distribution, and scan again until the laying situation is consistent with the actual situation; g. According to the designed precipitation intensity and precipitation time, simulate the real precipitation process on the 3D printed model; h. During precipitation, the Froude number is calculated by the precipitation velocity. If the Froude number is in the range of 0.5-7.6, it is judged to be similar to the watershed to be estimated; i. After the precipitation stops, wait for the solid material to be transported, obtain the total amount of simulated debris flow solid material, and perform post-disaster three-dimensional laser scanning on the 3D printed model to obtain the post-disaster DEM; j. The total amount of solid matter in the debris flow is magnified by the cube of x as the lower limit, and the DEM after the disaster is subtracted from the DEM before the disaster by the cube of x as the upper limit to obtain the estimated scale of the debris flow.

2. The debris flow scale estimation method according to claim 1, characterized in that: In the step a, a drone equipped with a laser radar is used to take aerial photos of the entire watershed, and the drone supporting software is used for post-processing to obtain a high-precision watershed terrain DEM; or a DEM produced by the French Pleiades satellite with an accuracy of 2m is directly purchased.

3. The debris flow scale estimation method according to claim 2, characterized in that: In step a, the source area is determined by remote sensing interpretation of aerial photography or satellite images; the source thickness is determined by on-site investigation or use of geological radar.

4. The method for estimating the scale of debris flow according to claim 3, characterized in that: In step a, the particle size distribution, density and natural water content of the source of the watershed to be estimated are investigated on site; the precipitation intensity of different frequencies in the area is obtained by querying i and time t .

5. The method for estimating the scale of debris flow according to claim 4, characterized in that: In step f, the source distribution includes source quantity, location and thickness.

6. The method for estimating the scale of debris flow according to claim 5, characterized in that: In step g, the precipitation intensity and precipitation time are scaled down by x^(1 / 2) times of the actual precipitation intensity and precipitation time of the basin to be estimated.

7. The method for estimating the scale of debris flow according to claim 6, characterized in that: In the step h, the precipitation process is recorded by video, and a pigment is used as a tracer to measure the precipitation velocity at the mountain pass, and the Froude number is calculated based on the precipitation velocity.

8. The method for estimating the scale of debris flow according to claim 7, characterized in that: In the step h, if the calculated Froude number is not in the range, the test is repeated until the obtained Froude number is in the range of 0.5-7.

6.

9. The method for estimating the scale of debris flow according to claim 8, characterized in that: In step j, the erosion amount and erosion distribution information of the debris flow are obtained according to the estimated debris flow scale, and the image range of the debris flow is outlined based on the erosion distribution information to obtain the area that may be affected by the debris flow.

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