Ramms-based debris flow dynamics simulation analysis and treatment evaluation method

Abstract

The application discloses a method for simulating and analyzing debris flow dynamics and evaluating treatment based on RAMMS. The simulation analysis method comprises the following steps: obtaining a debris flow geographic information file containing debris flow basic parameters and / or material source data in a debris flow basin; obtaining measured debris flow dynamics parameters of key positions based on measured data; importing a geographic model and the debris flow geographic information file into RAMMS to obtain a debris flow RAMMS geographic model; simulating and inverting the debris flow RAMMS geographic model through hydraulic release start and material source release start respectively according to simulation parameters and the measured debris flow dynamics parameters to obtain the required material source amount of the key positions under different rainfall frequencies and material source release start. The application can accurately simulate the dynamics process of the debris flow and accurately evaluate the effectiveness of the debris flow treatment scheme according to the simulation model.

Description

Technical Field

[0001] This invention relates to the technical field of debris flow disaster prevention and control, and in particular to a method for debris flow dynamic analysis and treatment scheme evaluation through numerical simulation. Background Technology

[0002] In recent years, with the deepening research on the movement characteristics of debris flows by scholars both domestically and internationally, various methods have been applied to the analysis of debris flow movement characteristics, such as numerical simulation, statistical empirical modeling, and prediction methods combining GIS and empirical models. Among these, numerical simulation is more popular and has become more mature and accurate. Based on the conceptual model used in the model solution, numerical simulation methods can currently be broadly classified into three categories: particle-based, strip-based, and continuous-medium-based numerical simulation methods. When applied to debris flow simulation analysis, particle-based numerical simulation methods treat debris flows as a medium composed of a large number of particles, and its movement characteristics are characterized by the movement characteristics of individual particles, with its mechanical properties determined by the interactions between particles. Strip-based numerical simulation methods treat debris flows as a group of adjacent, variable-shape but constant-volume strips, simulating the kinetic energy transfer process based on the interactions between strips and between strips and the substrate. Continuous-medium-based numerical simulation methods treat debris flows as non-Newtonian fluids, deriving the governing equations through depth homogenization while maintaining the conservation of mass and momentum.

[0003] The above methods for simulating debris flow processes do not take into account the distribution of sediment sources within the watershed, and the simulation results usually differ significantly from theoretical calculations.

[0004] In addition, existing simulation methods often use the results of rainwater runoff calculations or actual measurements as the input function for debris flow discharge, and then simulate the movement process of debris flow based on DEM topographic files. The above methods ignore the initiation location and initiation process of debris flow, and can only show the flow process of debris flow, but cannot obtain better prevention and control solutions. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to propose a debris flow dynamics simulation and analysis method and a debris flow control evaluation method based on RAMMS (Rapid Mass Movement Simulation) software. This method fully considers the distribution of material sources within the watershed and the debris flow initiation process, can accurately simulate the dynamic process of debris flow, and can accurately evaluate the effectiveness of debris flow control schemes based on the simulation model.

[0006] The technical solution of the present invention is as follows:

[0007] The RAMMS-based method for simulating and analyzing debris flow dynamics includes:

[0008] A debris flow simulation and analysis model was constructed based on RAMMS software.

[0009] The debris flow dynamics process in the study area was simulated and analyzed using the debris flow simulation analysis model to obtain its simulated dynamic parameters.

[0010] The construction of the debris flow simulation analysis model includes:

[0011] S1 obtains a debris flow geographic information file containing field survey data that can be recognized by RAMMS software. The field survey data includes basic debris flow parameters within the study area and / or source data within the debris flow basin. The source data includes source type, source distribution location, source distribution range, source static storage thickness, and source quantity. The basic debris flow parameters include basin area, average longitudinal gradient of the channel, debris flow unit weight, channel roughness coefficient, channel blockage coefficient, channel width, and local rainfall intensity.

[0012] S2 selects the proposed project location or important location within the ditch within the study area as key locations. Based on the field survey data, the dynamic parameters of debris flow at different rainfall frequencies at the key locations within the study area are obtained through the normative formula and the rainwater correction method. These are the measured dynamic parameters of debris flow, which include the mud depth, flow velocity, impact force, volume of debris flow ejected in one go, and volume of solid debris flow ejected in one go at different rainfall frequencies.

[0013] S3 imports the geographic model of the study area into the RAMMS software and loads the debris flow geographic information file onto the imported geographic model to obtain the debris flow RAMMS geographic model of the study area.

[0014] S4 sets the simulation parameters of the debris flow RAMMS geographic model, including its Coulomb friction coefficient μ and turbulent friction coefficient ξ;

[0015] S5, under the simulation parameters determined in S4, sets the debris flow initiation mode to hydraulic release initiation in the debris flow RAMMS geographic model, obtains the dynamic simulation parameters of the key location under different rainfall frequencies, and based on the dynamic simulation parameters and the measured debris flow dynamic parameters, sets the debris flow initiation mode to source release initiation in the debris flow RAMMS geographic model, and obtains the source amount required for source release initiation at the key location under different rainfall frequencies through model inversion;

[0016] Based on the amount of material source required for the release of material source at the key location under different rainfall frequencies obtained in S5, S6 sets the debris flow initiation mode to material source release in the debris flow RAMMS geographic model, and performs numerical simulation of the debris flow dynamics process at the key location under different rainfall frequencies to obtain the verified simulation dynamic parameters.

[0017] According to some preferred embodiments of the present invention, S1 includes:

[0018] The source data of the material within the study area were obtained through on-site investigation;

[0019] The distribution location and distribution range of the material sources in the material source data are vectorized using terrain processing software to obtain a vectorized file, which is then imported into the ArcGIS platform.

[0020] In the ArcGIS platform, the static storage thickness of the material source in the material source data is used as the initial material source activatable thickness, and the resulting file is converted into a shapefile file that can be recognized by RAMMS software.

[0021] According to some preferred embodiments of the present invention, the geographic model is a digital elevation model.

[0022] According to some preferred embodiments of the present invention, S4 includes:

[0023] Set the maximum Coulomb friction coefficient and maximum turbulent friction coefficient provided by RAMMS software as the initial values ​​for the Coulomb friction coefficient and the turbulent friction coefficient;

[0024] Based on the initial values, the values ​​of the Coulomb friction coefficient and the turbulent friction coefficient are adjusted according to the gradient to obtain the RAMMS software simulation results after each adjustment.

[0025] The simulation results of RAMMS software after each adjustment were compared with the mud depth, flow velocity and accumulation range obtained from the field survey data. The Coulomb friction coefficient and turbulent friction coefficient corresponding to the best match between the two were used as the final simulation parameters.

[0026] According to some preferred embodiments of the present invention, S5 includes:

[0027] S51 selects any key location upstream as the hydraulic release point, simulates the debris flow dynamics process at the hydraulic release point under different rainfall frequencies using the debris flow RAMMS geographical model, and obtains the simulated dynamic parameters of another key location downstream of the key location.

[0028] S52 compares the simulated dynamic parameters of this other key location with the measured debris flow dynamic parameters obtained through S2, and confirms the reliability of the simulation process based on the comparison.

[0029] S53 multiplies the static storage thickness of the material source in the material source data by the thickness reduction coefficient under different rainfall frequencies to obtain the material source initiation thickness of the material source release point. The thickness reduction coefficient is obtained by: setting an initial thickness reduction coefficient at any rainfall frequency, adjusting it based on the initial thickness reduction coefficient to obtain the material source initiation thickness after each adjustment, i.e., the material source adjustment initiation thickness; simulating the debris flow dynamics process of the material source release point under the material source adjustment initiation thickness using the debris flow RAMMS geographic model, obtaining the simulated dynamic parameters of any key location, comparing the simulated dynamic parameters with the simulated dynamic parameters obtained by S51 at the same rainfall frequency for the key location, and the thickness reduction coefficient corresponding to the material source adjustment initiation thickness when the two are consistent is the thickness reduction coefficient at that rainfall frequency.

[0030] S54 Based on the obtained material source initiation thickness and the distribution range of the material source obtained from the field investigation, the dynamic process of the debris flow is simulated in the debris flow RAMMS geographic model to obtain the simulated dynamic parameters under the material source release initiation mode.

[0031] S55 compares the simulated dynamic parameters of the material source release initiation mode obtained from multiple key locations with the measured debris flow dynamic parameters obtained from S2, fine-tunes the material source thickness based on the comparison, and obtains the amount of material source required for the release initiation of the key locations under different rainfall frequencies based on the adjusted debris flow RAMMS geographical model.

[0032] The present invention further provides a debris flow control assessment method based on RAMMS, which obtains the effectiveness assessment results of the control scheme for debris flow prevention and control through the above-mentioned debris flow simulation analysis model.

[0033] According to some preferred embodiments of the present invention, the debris flow control assessment method includes:

[0034] S71 obtains the reduced bulk density and reduced blockage rate of debris flow under different levels of effectiveness, wherein the level of effectiveness includes local effectiveness, partial effectiveness and overall effectiveness;

[0035] S72 Based on the reduced bulk density and reduced blockage rate of debris flow under different levels of effectiveness, the hydraulic release start-up method is adopted in the debris flow simulation analysis model to simulate the debris flow dynamic process at the key location under different rainfall frequencies, and obtain its simulated dynamic parameters.

[0036] S73 adjusts the geographical model of the study area according to the governance plan to obtain the corresponding adjusted debris flow RAMMS geographical model.

[0037] S74 sets the material source initiation thickness based on the amount of material source required to initiate the release of material source at the key location determined in S5 under different rainfall frequencies. Under this material source initiation thickness, the debris flow dynamics process at the key location under different rainfall frequencies is simulated by means of material source release initiation through the adjusted debris flow RAMMS geographical model to obtain its simulated dynamic parameters. The effectiveness of the treatment scheme is determined by comparing the obtained simulated dynamic parameters with the design parameters and / or the calculation amount of the treatment scheme.

[0038] The present invention has the following beneficial effects:

[0039] (1) The simulation analysis method of the present invention overcomes the shortcomings of conventional numerical simulation methods that only consider the flow state of debris flow and ignore the debris flow initiation process. By releasing the material source in RAMMS, the dynamic process of debris flow outbreak is simulated more realistically. It not only considers the initiation method and volume of the material source, but also the influence of the distribution of each material source on the design of the control project.

[0040] (2) The evaluation method of the present invention can fully verify and evaluate the treatment effect of the treatment scheme such as the barrier project. Specifically, it can verify the impact of the treatment project by considering the reduced bulk density and blockage coefficient and using hydraulic release, and obtain the debris flow dynamic characteristic values ​​of each key section after the implementation of the treatment project. It can also verify the impact of the treatment project by setting the dam position and using material source release. Attached Figure Description

[0041] Figure 1 This is a flowchart of the debris flow dynamics simulation and analysis method based on RAMMS in Example 1.

[0042] Figure 2 This is a schematic diagram showing the key cross-sectional locations and the distribution and range of the main material sources in Example 1. Detailed Implementation

[0043] The present invention will now be described in detail with reference to embodiments and accompanying drawings. However, it should be understood that the embodiments and drawings are for illustrative purposes only and do not constitute any limitation on the scope of protection of the present invention. All reasonable modifications and combinations included within the inventive spirit of the present invention fall within the scope of protection of the present invention.

[0044] Example 1

[0045] This embodiment uses Liandenggou in Jinding Town, Lanping County, Yunnan Province as an example to simulate its debris flow dynamics. (Refer to...) Figure 1The debris flow dynamics simulation and analysis method used includes the following steps:

[0046] S1. Obtain a debris flow geographic information file containing field survey data. This file can be recognized by RAMMS software and specifically includes:

[0047] The basic parameters of debris flow and the source data of debris flow in the debris flow basin were determined through field investigation. The source data includes source type, source distribution location, source distribution range, source static storage thickness, and source quantity. The basic parameters of debris flow include basin area, average longitudinal gradient of the channel, debris flow unit weight, channel roughness coefficient, channel blockage coefficient, channel width, and local rainfall intensity. Among them, the source refers to loose solid material that can participate in debris flow activities.

[0048] The distribution location and range of the material sources are vectorized using terrain processing software such as Ovi Interactive Map, and the resulting vectorized file is then imported into ArcGIS.

[0049] In ArcGIS, the static reserve thickness of the material source is used as the initial activating thickness of the material source, and the file is converted into a shapefile that can be recognized by RAMMS software.

[0050] S2. Select the location of the proposed project or an important location within the trench as the critical location. See below for the locations of each critical profile. Figure 2 Based on the aforementioned field survey data, the dynamic parameters of debris flows at key locations within the study area under different rainfall frequencies were obtained using standardized formulas and the rainwater correction method. These are the measured dynamic parameters of debris flows, including the mud depth, flow velocity, impact force, volume ejected in a single run, and volume ejected solids in a single run under different rainfall frequencies. Specifically, these parameters include:

[0051] Based on the hydrological data of the study area, field measurement results, and relevant survey and design specifications (in this embodiment, the "Sichuan Province Small and Medium Watershed Rainstorm Flood Calculation Manual" and the "Debris Flow Disaster Prevention and Control Engineering Survey Specification" were specifically used), debris flow dynamic parameters such as mud depth, flow velocity, flow rate, and single-pass scale under different rainfall frequencies were calculated, and the obtained debris flow dynamic parameters were used as the basis for setting RAMMS model parameters.

[0052] Specifically, see attached Figure 2 Taking the critical location #33 as an example, the calculation process of its debris flow dynamic parameters is as follows:

[0053] (1) Flow velocity calculation

[0054] Based on the on-site investigation, the Liandenggou debris flow was identified as a viscous debris flow. The flow velocity calculation formula for viscous debris flows, recommended in the "Code for Investigation of Debris Flow Disaster Prevention Engineering" (DZ / T0220-2006), was used for calculation.

[0055]

[0056] Where Vc – debris flow velocity; Hc – average debris flow depth; Ic – longitudinal slope of the channel bed; 1 / n – riverbed roughness coefficient, taken from Table 1:

[0057] Table 1. Reference Table for Roughness Coefficient n of Viscous Debris Flow Channels

[0058]

[0059] Based on the actual investigation, the debris flow velocity at profile #33 was determined as follows:

[0060] Table 2 Calculation results of flow velocity in section 33#

[0061] Average mud depth Hc (m) 1.24 1.35 1.46 Natural channel roughness coefficient Mc = 1 / n 183.38 183.38 183.38 The longitudinal gradient of the main ditch is Ic (‰). 13.00 13.00 13.00 <![CDATA[Debris flow velocity V C (m / s)]]> 6.42 6.81 7.16

[0062] (2) Flow calculation

[0063] The debris flow discharge was calculated using the rainwater correction method. When calculating the peak debris flow discharge using the rainwater correction method, the peak discharge of the watershed rainstorm was calculated first, and then the peak debris flow discharge was calculated.

[0064] The peak discharge of the watershed during rainstorms is calculated using the formula recommended in the "Sichuan Province Small and Medium Watershed Rainstorm and Flood Calculation Manual":

[0065]

[0066] in:

[0067] ψ=f(μ,τ n )

[0068] τ n =f(m,s,J,L)

[0069] In the formula: Q p —Design flow rate for rainstorm floods with frequency p (m³) 3 / s); ψ—peak runoff coefficient; s—rainfall intensity (mm / h); n—rainfall index; F—drainage area (km²) 2 L—channel length (km); τ—watershed runoff time (h); μ—runoff generation parameter, i.e., average infiltration intensity of the watershed during the runoff generation period (mm / h); m—runoff generation parameter.

[0070] The parameter values ​​and calculations in the above formula are as follows:

[0071] 1) Calculation of the confluence parameter m:

[0072] First, calculate the watershed characteristic coefficient θ:

[0073]

[0074] Where: L—channel length, km; J—average longitudinal slope of the channel, ‰; F—watershed area, km² 2 .

[0075] The calculation results are shown in Table 3:

[0076] Table 3. Calculation results of characteristic parameter θ of the watershed at profile #33 in Liandenggou.

[0077]

[0078]

[0079] Based on the calculation results of the watershed characteristic parameter θ in the table above, and referring to the comprehensive result table of the confluence parameter m (Table 4), the calculation formula for the mountainous area of ​​southwestern Sichuan is adopted, and since θ is between 1 and 30, the confluence parameter m is as follows:

[0080] m = 0.221θ 0.204

[0081] Table 4. Comprehensive Results of Convergence Parameter m Values

[0082]

[0083] Typically, considering the unique topography of the watershed, the confluence parameters need to be adjusted, namely:

[0084] m′=Km

[0085] In the formula: m'—corrected bus parameter; K—bus parameter correction coefficient.

[0086] The values ​​of the confluence parameter correction coefficients are referenced in Table 5.

[0087] Table 5. Correction coefficient K value for merge parameters

[0088]

[0089] The calculated values ​​of the confluence parameter m for different profiles are shown in Table 6.

[0090] Table 6 Calculation results of the confluence parameter m of section 33#, Liandenggou

[0091] Section 33 4.91 0.22

[0092] 2) Calculation of runoff parameter μ

[0093] Referring to the comprehensive results table of runoff generation parameter μ in the "Sichuan Province Small and Medium Watershed Rainstorm Flood Calculation Manual" (Table 7), the Liandenggou watershed has a relative elevation difference of over 200m, steep terrain, deep incision, good vegetation, and some barren mountains or slopes. Therefore, the runoff generation parameter μ is:

[0094] μ = 6F -0.19

[0095] Table 7. Comprehensive Results of Runoff Generation Parameter μ Values ​​in Small Watersheds of Sichuan Province

[0096]

[0097] Table 8 Calculation results of runoff parameters μ at Liandenggou Section 33#

[0098] Section 33 8.09 4.03

[0099] 3) The calculation of the rainstorm parameter n and the rainstorm intensity S is as follows:

[0100] S = H tp t n-1

[0101] In the formula: H tp —Maximum hourly rainfall (mm) at the design frequency; t—Rainfall duration (h); n—Rainfall parameters.

[0102] The calculation formulas for the rainstorm parameters differ for different rainstorm durations, as shown in Table 9.

[0103] Table 9 Calculation Table of Rainstorm Parameter n

[0104]

[0105]

[0106] Based on the specific duration and parameters of the rainstorm, the rainstorm intensity at the design frequency can be calculated, as shown in Table 10.

[0107] Table 10 Calculation Table of Rainfall Intensity S in Heavy Rainfall

[0108]

[0109] According to the rainfall isopleth maps in the "Statistical Atlas of Rainfall Parameters in China" (2006 edition), the average annual maximum rainfall H for 10 min, 60 min, 6 h, and 24 h in the Liandenggou watershed is 12.00 mm, 30.00 mm, 45.00 mm, and 55.00 mm, respectively, with a coefficient of variation Cv of 0.33. The calculated results of the rainfall parameter n and maximum rainfall for the Liandenggou watershed using the above formula are shown in Table 11, and the calculated rainfall intensity S for profile #33 is shown in Table 12.

[0110] Table 11 Calculation Table of Design Maximum Rainfall and Rainfall Parameter n

[0111]

[0112] Table 12 Calculation results of rainfall intensity S during heavy rain at profile #33 in Liandenggou.

[0113]

[0114]

[0115] 4) Calculation of peak runoff coefficient χ

[0116] ① Calculate τ0 based on the relevant values ​​θ, m, and S obtained above:

[0117]

[0118] In the formula: τ0 is the watershed confluence time (h) when ψ=1.

[0119] Table 13 Calculation results of τ0 in section 33# of Liandenggou

[0120]

[0121] ② According to the formula in the "Sichuan Province Small and Medium Watershed Rainstorm and Flood Calculation Manual", the peak runoff coefficient ψ can be calculated using the following formula. The calculation results of the peak runoff coefficient ψ for profile #33 are shown in Table 14.

[0122]

[0123] Table 14 Calculation results of peak runoff coefficient ψ at Liandenggou Section 33#

[0124]

[0125] 5) Calculation of convergence time τ

[0126] According to the "Sichuan Province Small and Medium Watershed Rainstorm Flood Calculation Manual", the confluence time τ is calculated using the following formula, and the calculation results are shown in Table 15.

[0127]

[0128] Table 15 Calculation results of the confluence time τ at profile #33 of Liandenggou.

[0129]

[0130] 6) Calculation of peak flow rate during rainstorms

[0131] The calculation results of the peak flow of rainstorms in the Liandenggou debris flow basin are shown in Table 16.

[0132] Table 16 shows the calculation of peak storm discharge Qp at different locations and rainfall frequencies based on the stormwater runoff method.

[0133]

[0134] 7) Calculation of peak flow rate of debris flow

[0135] The peak flow rate of debris flows is calculated according to the "Specification for Investigation of Debris Flow Disaster Prevention and Control Engineering".

[0136] (DZ / T0220-2006), Appendix I Formula:

[0137]

[0138] In the formula: Q c —Peak flow rate of debris flow profile (m³) 3 / s); —The sediment correction factor, determined through field investigation, is 0.868; Q p —Peak flow rate during heavy rainfall, see Table 16; D c —Congestion coefficient.

[0139] The values ​​of the debris flow blockage coefficient are referenced in Table 17.

[0140] Table 17 Reference Values ​​for Debris Flow Blockage Coefficient

[0141]

[0142]

[0143] Based on the values ​​of the blockage coefficient, the debris flow rates under different profiles and different rainfall frequencies were calculated, as shown in Table 18.

[0144] Table 18 Debris flow rate under different profiles and rainfall frequencies

[0145]

[0146] (3) Total amount of a single debris flow process

[0147] 1) Total amount of a single debris flow event

[0148] The total flow volume of a single debris flow is calculated according to the calculation formula provided in Appendix I of the "Specification for Investigation of Debris Flow Disaster Prevention and Control Engineering" (DZ / T0220-2006).

[0149] Q = 0.264TQ c

[0150] Where: Q—the total volume of a single debris flow (m³) 3 T—dust duration of debris flow (s); Q c— Peak flow rate of debris flow (m³) 3 / s). T value explanation: The duration of the debris flow is determined based on the historical times of debris flows observed on-site. Here, the duration is taken as 5400s.

[0151] 2) Total amount of solid material discharged in one flush

[0152] Solid ejecta from a single debris flow shall be handled in accordance with the "Specifications for Investigation of Debris Flow Disaster Prevention and Control Engineering".

[0153] The calculations are performed using the formulas provided in Appendix I of (DZ / T0220-2006):

[0154] Q H =Q(γ) c -γ w ) / (γ H -γ w )

[0155] In the formula: Q H —Total amount of solid material ejected by a single mudslide (m³) 3 Q—total volume of a single debris flow event (m³) 3 );γ c —Severity of debris flow (t / m 3 ), with a value of 1.76; γ w —Specific gravity of water (t / m³) 3 ), taking the value 1; γ H —Specific gravity of solid material in debris flow (t / m³) 3 ), with a value of 2.65.

[0156] The results of the total amount of debris flow and the total amount of solid material ejected in one run were verified using key profiles. Table 19 shows the results of the total amount of debris flow and solid material ejected in one run at profile #33.

[0157] Table 19 Calculation of the total amount of debris flow in a single debris flow process at section 33#

[0158] <![CDATA[Total volume of a debris flow Q(10 4 m 3 )]]> 20.41 23.63 26.83 <![CDATA[Total mass of solid material flushed out in one time Q H (10 4 m 3 )]]> 9.39 10.87 12.34

[0159] S3 imports the geographic model of the study area into the RAMMS software and loads the debris flow geographic information file onto the imported geographic model to obtain the debris flow RAMMS geographic model of the study area, specifically including:

[0160] The measured contour lines (CAD files with an accuracy of 1m) of the Liandeng debris flow gully basin were converted into a digital elevation model using ArcGIS, then converted into an ASCII format file, imported into RAMMS software, and the shapefile file obtained by S1 was loaded onto the imported file.

[0161] S4. Set the simulation parameters of the debris flow RAMMS geographic model, including its Coulomb friction coefficient (μ) and turbulent friction coefficient (ξ).

[0162] The specific settings for the Coulomb friction coefficient (μ) and the turbulent friction coefficient (ξ) are as follows:

[0163] Set the maximum Coulomb friction coefficient and maximum turbulent friction coefficient provided by RAMMS software as their initial values, such as the range given by the software: μ: 0.05~0.4m / s. 2 ξ: 200~1000m / s 2 Therefore, the initial values ​​for the Coulomb friction coefficient and the turbulent friction coefficient are set to 0.4 m / s². 2 and 1000m / s 2 ;

[0164] Based on the initial values, the values ​​of the Coulomb friction coefficient and the turbulent friction coefficient are adjusted according to the gradient to obtain the RAMMS software simulation results after each adjustment.

[0165] The simulation results of RAMMS software after each adjustment were compared with the measured mud depth, flow velocity, and accumulation range. The Coulomb friction coefficient and turbulent friction coefficient corresponding to the best match between the two were used as the final simulation parameters.

[0166] In this embodiment, the gradient adjustment method involves changing the value of μ by ±0.01 and the value of ξ by ±20 each time. The final simulation parameters are determined to be μ = 0.06 m / s. 2 ξ=200m / s 2 .

[0167] S5. Under the simulation parameters determined in S4, select hydraulic release start-up as the debris flow initiation method in RAMMS software to obtain the simulation results of the key location. Under the simulation results, select material source release start-up as the debris flow initiation method in RAMMS software. Through model inversion, obtain the amount of material source required for material source release start-up at the key location under different rainfall frequencies.

[0168] RAMMS software provides two default debris flow initiation methods: hydraulic release initiation, which initiates the debris flow by releasing a flow rate at a given location based on the relationship between flow rate and time; and source release initiation, which attributes the entire debris flow occurrence to the transformation of the source, initiating the debris flow based on the given source distribution location and thickness. This embodiment utilizes the two built-in debris flow initiation methods in RAMMS. Based on the simulation results obtained under the hydraulic release initiation method, the source release initiation method is used to simulate and invert the required source quantity for source release initiation under different rainfall frequencies in Liandenggou.

[0169] This embodiment specifically employs the following steps:

[0170] S51: Considering that most of the sediment sources in Liandeng Gully are concentrated in the upstream gully of section 33#, and section 33# itself is a key section in the design, section 33# is used as a typical section to determine the sediment release amount. Sections 1# and 19# are used as hydraulic release points to conduct dynamic simulations under different rainfall frequencies, and obtain the simulated dynamic parameters of the downstream section 33#, including its debris flow velocity, flow rate, and total amount of a single process.

[0171] S52: Compare the simulated dynamic parameters at section 33 with the measured debris flow dynamic parameters at section 33 obtained from S2 to confirm the reliability of the numerical simulation results.

[0172] S53 uses the static storage thickness of the source obtained from the field investigation multiplied by the thickness reduction coefficient under different rainfall frequencies as the starting thickness of the source for the two profiles under different rainfall frequencies. The thickness reduction coefficient can be initially set to 0.5. Subsequently, based on the dynamic simulation results of the source starting and release mode, the thickness reduction coefficient is continuously calculated and adjusted to adjust the starting amount of the source. After each adjustment, the simulated dynamic parameters of the downstream 33# profile are compared with the simulated dynamic parameters of the hydraulic starting and release mode obtained through S51. When the two are consistent, the thickness reduction coefficient of each source is determined.

[0173] S54: After obtaining the starting amount of each material source, the dynamic process of debris flow is simulated in RAMMS using the material source starting and releasing method.

[0174] S55 simulates and verifies the cross-sections of the upstream controlling main and tributary gullies sequentially, and compares the results with those calculated in S2 to further verify the rationality of the sediment source initiation amount at each location. Unreasonable sediment source thicknesses are fine-tuned, and the initiation amount and proportion of each sediment source in the debris flow basin under different rainfall frequencies are finally determined, as shown in Table 20 below:

[0175] Table 20 Estimated Starting Volume of Liandeng Ditch Bed and Deposits on Both Sides of the Ditch Bed

[0176]

[0177] S6. Based on the determination of the source release amount under different rainfall frequencies in S5, the debris flow movement process under different rainfall frequencies is simulated using the source release method. The simulated debris flow dynamic parameters obtained at different times, such as debris flow depth, flow velocity, overall impact force changes, and debris flow influence range, are recorded as shown in Table 21 below:

[0178] Table 21 Numerical simulation results of characteristic parameters of natural gully dynamics before the Liandenggou debris flow control project.

[0179]

[0180] Note: Qc is the debris flow rate, Vc is the debris flow velocity, Hc is the debris flow depth, and F... S This refers to the impact force of a debris flow.

[0181] S7 obtains a debris flow simulation analysis model through the construction process of S1-S6. The effectiveness of the control project is then analyzed using this model, specifically including:

[0182] After the control project is implemented, the reduced bulk density and blockage coefficient are used in the simulation analysis model to simulate the debris flow dynamics of Liandenggou by hydraulically releasing debris flow, so as to verify the effect of the control project. Alternatively, a barrier dam can be set in RAMMS and debris flow can be simulated by releasing material source to verify the effect of the control project.

[0183] In this embodiment, S7 specifically includes:

[0184] S71: Determine the reduced bulk density and blockage factor for debris flows, including:

[0185] Based on the implementation of debris flow control projects, the effectiveness of these projects can be categorized into three levels: locally effective, partially effective, and globally effective. Locally effective projects only control small landslides within the gully, leaving a significant possibility of debris flow blockage. The control system for preventing damming is incomplete, resulting in only moderate effectiveness. Partially effective projects target the main initiating debris sources within the gully, effectively preventing medium and large landslides from blocking the gully. However, the possibility of medium and small landslides still exists, and the control system for preventing damming is basically complete, resulting in good effectiveness. Globally effective projects comprehensively control all large, medium, and small landslides that could potentially trigger damming within the gully, minimizing the likelihood of debris flow damming. The control system for preventing damming is complete, resulting in good effectiveness. The reduced bulk density of debris flows after implementing these three levels of effectiveness is 1.60–1.80 t / m³, respectively. 3 1.40~1.60t / m 3 1.20~1.40t / m 3 The corresponding reduction rates for the blockage coefficients are 0.9–1.0, 0.7–0.9, and 0.5–0.7, respectively (reduced blockage coefficient = reduction rate of blockage coefficient * original blockage coefficient).

[0186] S72: Using the reduced debris flow density and blockage coefficient, the debris flow dynamics of profile 33# under different rainfall frequencies were simulated in RAMMS by hydraulic release to initiate the debris flow. The simulation results of its dynamic parameters, such as flow rate and total amount of one process, were obtained, as shown in Table 22 below. According to Table 22, the debris flow rate and the scale of one flush were significantly reduced after the implementation of the control project in this embodiment, which proves the effectiveness of the control project.

[0187] Table 22 Comparison of the location of section #33 before and after the full implementation of the Liandenggou debris flow control project.

[0188]

[0189]

[0190] S73: Based on the design plan of the Liandenggou management project, determine the basic parameters such as the control point coordinates, dam length, and design elevation of the dam site area; based on the design parameters of the dam, obtain the topographic data of the additional dam by modifying the original contour lines and elevation points of the selected dam site area, and then generate a DEM from the topographic data; import the processed DEM into RAMMS software.

[0191] S74: Based on the dam parameters imported from S73, a geographic information model with dam data is obtained. According to the material source initiation amount determined in S5, the debris flow dynamics process under different rainfall frequencies is simulated in RAMMS using the material source release method. The total amount of debris flow in one process at profile 33# is determined and compared with the dam reservoir capacity to verify the effectiveness of the control project. Through simulation calculation, the Liandenggou dam control project has a good prevention and control effect on debris flow and meets the prevention and control requirements.

[0192] Table 23 Comparison of the location of section #33 before and after the full implementation of the Liandenggou debris flow control project.

[0193]

[0194] The above embodiments are merely preferred embodiments of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A RAMMS-based method for simulating and analyzing debris flow dynamics, characterized in that, It includes: A debris flow simulation and analysis model was constructed based on RAMMS software. The debris flow dynamics process in the study area was simulated and analyzed using the debris flow simulation analysis model to obtain its simulated dynamic parameters. The construction of the debris flow simulation analysis model includes: S1 obtains a debris flow geographic information file containing field survey data that can be recognized by RAMMS software. The field survey data includes basic debris flow parameters within the study area and source data within the debris flow basin. The source data includes source type, source distribution location, source distribution range, source static storage thickness, and source quantity. The basic debris flow parameters include basin area, average longitudinal gradient of the channel, debris flow unit weight, channel roughness coefficient, channel blockage coefficient, channel width, and local rainfall intensity. S2 selects the proposed project location or important location within the ditch within the study area as key locations. Based on the field survey data, the debris flow dynamic parameters at different rainfall frequencies are obtained through normative formulas and rainwater correction methods. These are the measured debris flow dynamic parameters, which include the mud depth, flow velocity, impact force, volume of debris flow ejected in one go, and volume of solids ejected in one go at different rainfall frequencies. S3 imports the geographic model of the study area into the RAMMS software and loads the debris flow geographic information file onto the imported geographic model to obtain the debris flow RAMMS geographic model of the study area. S4 sets the simulation parameters of the debris flow RAMMS geographic model, including its Coulomb friction coefficient μ and turbulent friction coefficient ξ; S5, under the simulation parameters determined in S4, sets the debris flow initiation mode to hydraulic release initiation in the debris flow RAMMS geographic model, obtains the dynamic simulation parameters of the key location under different rainfall frequencies, and based on the dynamic simulation parameters and the measured debris flow dynamic parameters, sets the debris flow initiation mode to source release initiation in the debris flow RAMMS geographic model, and obtains the source amount required for source release initiation at the key location under different rainfall frequencies through model inversion; Based on the amount of material source required for the release of material source at the key location under different rainfall frequencies obtained in S5, S6 sets the debris flow initiation mode to material source release in the debris flow RAMMS geographic model, and performs numerical simulation of the debris flow dynamics process at the key location under different rainfall frequencies to obtain the verified simulation dynamic parameters.

2. The debris flow dynamics simulation and analysis method according to claim 1, characterized in that, S1 includes: The source data of the material within the study area were obtained through on-site investigation; The distribution location and distribution range of the material sources in the material source data are vectorized using terrain processing software to obtain a vectorized file, which is then imported into the ArcGIS platform. In the ArcGIS platform, the static storage thickness of the material source in the material source data is used as the initial material source activatable thickness, and the resulting file is converted into a shapefile file that can be recognized by RAMMS software.

3. The debris flow dynamics simulation and analysis method according to claim 1, characterized in that, The geographic model is a digital elevation model.

4. The debris flow dynamics simulation and analysis method according to claim 1, characterized in that, S4 includes: Set the maximum Coulomb friction coefficient and maximum turbulent friction coefficient provided by RAMMS software as the initial values ​​for the Coulomb friction coefficient and the turbulent friction coefficient; Based on the initial values, the values ​​of the Coulomb friction coefficient and the turbulent friction coefficient are adjusted according to the gradient to obtain the RAMMS software simulation results after each adjustment. The simulation results of RAMMS software after each adjustment were compared with the mud depth, flow velocity and accumulation range obtained from the field survey data. The Coulomb friction coefficient and turbulent friction coefficient corresponding to the best match between the two were used as the final simulation parameters.

5. The debris flow dynamics simulation and analysis method according to claim 1, characterized in that, S5 includes: S51 selects any key location as the hydraulic release point, simulates the debris flow dynamics process of the hydraulic release point under different rainfall frequencies using the debris flow RAMMS geographical model, and obtains the simulated dynamic parameters of another key location downstream of the key location. S52 compares the simulated dynamic parameters of this other key location with the measured debris flow dynamic parameters obtained through S2 to confirm the reliability of the numerical simulation results. S53 multiplies the static storage thickness of the material source in the material source data by the thickness reduction coefficient under different rainfall frequencies to obtain the material source initiation thickness of the material source release point. The thickness reduction coefficient is obtained by: setting an initial thickness reduction coefficient at any rainfall frequency, adjusting it based on the initial thickness reduction coefficient to obtain the material source initiation thickness after each adjustment, i.e., the material source adjustment initiation thickness; simulating the debris flow dynamics process of the material source release point under the material source adjustment initiation thickness using the debris flow RAMMS geographic model, obtaining the simulated dynamic parameters of any key location, comparing the simulated dynamic parameters with the simulated dynamic parameters obtained by S51 at the same rainfall frequency for the key location, and the thickness reduction coefficient corresponding to the material source adjustment initiation thickness when the two are consistent is the thickness reduction coefficient under that rainfall frequency. S54 Based on the obtained material source initiation thickness, the dynamic process of the debris flow is simulated in the debris flow RAMMS geographic model to obtain the simulated dynamic parameters under the material source release initiation mode. S55 compares the simulated dynamic parameters of the material source release initiation mode obtained from multiple key locations with the measured debris flow dynamic parameters obtained from S2. Based on the comparison, the thickness of the material source point is finely adjusted. Based on the adjusted debris flow RAMMS geographic model, the amount of material source required for the release initiation of the material source at the key locations under different rainfall frequencies is obtained.

6. A RAMMS-based debris flow control assessment method, which obtains the effectiveness assessment results of the control scheme for debris flow prevention and control through the debris flow simulation analysis model according to any one of claims 1-5.

7. The debris flow control assessment method according to claim 6, characterized in that, It includes: S71 obtains the reduced bulk density and reduced blockage rate of debris flow under different levels of effectiveness, wherein the level of effectiveness includes local effectiveness, partial effectiveness and overall effectiveness; S72 Based on the reduced bulk density and reduced blockage rate of debris flow under different levels of effectiveness, the hydraulic release start-up method is adopted in the debris flow simulation analysis model to simulate the debris flow dynamic process at the key location under different rainfall frequencies, and obtain its simulated dynamic parameters. S73 adjusts the geographical model of the study area according to the governance plan to obtain the corresponding adjusted debris flow RAMMS geographical model. S74 sets the material source initiation thickness based on the amount of material source required to initiate the release of material source at the key location determined in S5 under different rainfall frequencies. Under this material source initiation thickness, the debris flow dynamics process at the key location under different rainfall frequencies is simulated by means of material source release initiation through the adjusted debris flow RAMMS geographical model to obtain its simulated dynamic parameters. The effectiveness of the treatment scheme is determined by comparing the obtained simulated dynamic parameters with the design parameters and / or the calculation amount of the treatment scheme.

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