A method for predicting peak discharge of moraine dam outburst considering the influence of buried ice

Abstract

The present invention relates to the technical field of disaster prevention and reduction, and in particular to a method for predicting peak flow of moraine dam burst considering the influence of buried ice. The prediction method uses ice content, ice melting degree, and ice particle size as buried ice parameters that characterize the influence of buried ice on the peak flow of moraine dam burst, and uses them as one of the variables affecting the moraine dam burst flow to study, thereby optimizing the moraine dam burst peak flow prediction model, improving the model prediction accuracy, and filling the gap in the prediction method of the peak flow of moraine dam burst containing ice.

Description

Technical Field

[0001] The present invention relates to the technical field of disaster prevention and reduction, and in particular to a method for predicting peak flow rate of moraine dam breach taking into account the influence of buried ice. Background Art

[0002] Moraine dams are the result of glaciers advancing and eroding the surface, and transporting and accumulating the debris formed by the erosion. Moraine dams are mostly located in high and cold mountainous areas at mid- and low-latitudes. They are usually formed by the deposition of poorly classified moraine soil particles under the action of gravity. When the altitude is high, they may contain remnants of glacial ice, that is, buried ice.

[0003] Once a moraine dam fails, a drastic energy conversion will occur under the condition of high altitude drop, and the flood or debris flow caused by the failure will pose a very serious threat to the downstream. Many teams at home and abroad have conducted research on the outburst flow of moraine lakes and obtained the regression formula for the peak outburst flow, such as: Kirkpatrick (Kirkpatrick, GA, 1977. Evaluation guidelines for spillway adequacy. In: The Evaluation of Dam Safety, Proc. Eng. Found. Conf., New York, Am. Soc. Civ. Eng., pp. 395-414.) Based on the dam height H in 21 historical and hypothetical breach events, the calculation formula for the peak outburst flow is obtained: Q m =2.297(H+1) 2.5 ; The American Society of Soil and Water Conservation (Liu Ning, Cheng Zunlan, Cui Peng, Chen Ningsheng, et al. 2013. Landslide-dammed lakes and their risk control. Beijing: Science Press, pp. 141-142.) revised the above formula through another 13 breaches to: Q m =65H 1.85 , and through 31 dam failure events with dam heights ranging from 1.8 to 84 m, the formula was revised to: Q m =48H 1.63 ; The Chinese invention patent with publication number CN107016185A also discloses a calculation method for predicting the peak flow of moraine lake outburst floods.

[0004] The existing technologies have not considered the impact of buried ice on the outburst flow of moraine dams. When there is buried ice inside the dam body of a moraine dam, the dam body is more sensitive to the ambient temperature: when the ambient temperature rises, the buried ice inside the dam body melts, thereby affecting the physical and mechanical environment of the dam body structure and materials, and destroying the stability of the dam body. In reality, there are many cases where the temperature rise causes the buried ice to melt and then induces the dam body to burst. In addition, during the process of moraine dam burst, the special properties of ice will have a certain impact on the flow change during the burst.

[0005] Therefore, it is necessary to establish a method for predicting the peak flow of moraine dam outburst considering the influence of buried ice to improve the prediction accuracy. Summary of the invention

[0006] In view of the deficiency that the existing technology does not consider the influencing factor of buried ice when predicting moraine dam burst flow, the purpose of the present invention is to provide a method for predicting the peak flow of moraine dam burst taking into account the influence of buried ice, and taking ice content, ice melting degree and ice particle size as buried ice parameters to characterize the influence of buried ice on the peak flow of moraine dam burst, and taking it as one of the variables affecting the moraine dam burst flow to study, thereby optimizing the moraine dam burst peak flow prediction model, improving the model prediction accuracy, and filling the gap in the prediction method of the peak flow of moraine dam burst containing ice.

[0007] The present invention provides a method for predicting the peak flow rate of moraine dam burst considering the influence of buried ice. The ice content, ice melting degree and ice particle size are used as buried ice parameters for characterizing the influence of buried ice on the peak flow rate of moraine dam burst. Through simulation experiments, adjustment coefficients and amplification coefficients are obtained to characterize the influence of ice content, ice melting degree and ice particle size on the peak flow rate of moraine dam burst. Then, the adjustment coefficients and amplification coefficients are brought into a moraine dam burst peak flow prediction model to predict the peak flow rate of moraine dam burst.

[0008] It should be noted that the prediction results of the present invention include two peak burst flows, one is the peak burst flow when the ice in the moraine dam does not melt, and the other is the peak burst flow when the ice in the moraine dam melts. In order to more conveniently distinguish the two peak burst flows, the peak burst flow when the ice does not melt is used as the peak burst flow of the dam body. Q p Characterize the maximum peak flow rate under ice melting conditions Q p * express.

[0009] Furthermore, in order to better implement the present invention, the ice content is characterized by the volume fraction of buried ice; wherein the volume fraction of buried ice is the percentage of the volume of buried ice inside the dam body to the total volume of the dam body.

[0010] Furthermore, in order to better implement the present invention, the ice particle size is characterized by the average particle size of buried ice.

[0011] Furthermore, in order to better realize the present invention, the amplification factor is used to characterize the ratio of the maximum peak burst flow when the ice melts and the peak burst flow when the ice does not melt under the same working conditions; the amplification factor is calculated by the dam body height and the coarse particle content of the dam body.

[0012] Furthermore, in order to better implement the present invention, the coarse particle content of the dam body is characterized by the median particle size of the dam body particles.

[0013] Furthermore, in order to better implement the present invention, the method for obtaining the adjustment coefficient specifically refers to:

[0014] Firstly, a series of miniature models were built to simulate the actual moraine dam to simulate the moraine dam breach state and obtain the peak breach flow. The values ​​of the buried ice parameters inside the dam bodies of each miniature model were not exactly the same.

[0015] Then, the dam height, dam bottom length, gravitational acceleration, ice content, ice particle size, median particle size of dam particles, maximum particle size of dam particles, and dam porosity ratio are used as variables for simulating the breach state of moraine dam, and a prediction expression for the breach peak flow is obtained based on the dimensional analysis method and the multivariate regression analysis method; the prediction expression for the breach peak flow is composed of the variables for simulating the breach state of moraine dam and the adjustment coefficient;

[0016] Finally, simulation experiments were carried out on a series of miniature models to obtain experimental data consisting of multiple groups of variable values ​​with different numerical values. Nonlinear fitting was performed using the Levenberg-Marquardt algorithm to obtain the value of the adjustment coefficient.

[0017] Furthermore, in order to better realize the present invention, the experimental device used in the simulation experiment includes a water supply device, a water collecting tank, a water trough, a waste pool and a moraine dam model; the water trough is provided with a moving bed to avoid boundary seepage caused by direct contact between soil particles and smooth boundaries.

[0018] Further, in order to better implement the present invention, the raw materials of the moraine dam model include moraine soil and ice blocks;

[0019] The method for making the moraine dam model is: ice blocks in a frozen state are randomly distributed in loose moraine soil and piled up to form the moraine dam model.

[0020] Furthermore, in order to better implement the present invention, the experimental equipment used in the simulation experiment includes a camera, a water pressure sensor and a data acquisition instrument.

[0021] The beneficial effects of the present invention are as follows.

[0022] (1) The present invention provides a method for predicting the peak flow rate of moraine dam outburst considering the influence of buried ice. The ice content, ice melting degree and ice particle size are used as buried ice parameters to characterize the influence of buried ice on the peak flow rate of moraine dam outburst, and are studied as one of the variables affecting the outburst flow of moraine dam, thus filling the gap in the method for predicting the peak flow rate of moraine dam outburst containing ice.

[0023] (2) The present invention provides a method for predicting the peak flow rate of moraine dam outburst taking into account the influence of buried ice. The moraine dam outburst peak flow rate prediction model is optimized based on buried ice parameters to improve the prediction accuracy.

[0024] (3) The present invention provides a method for predicting the peak flow rate of moraine dam outburst considering the influence of buried ice, which can provide a reference for the prevention, control and mitigation of moraine dam outburst disasters in high-altitude mountainous areas.

[0025] (4) This paper proposes a method for predicting the peak flow rate of moraine dam breach considering the influence of buried ice. This method is based on real and effective experimental data and uses dimensional analysis and regression analysis as the main analytical methods to ensure the scientific nature of the prediction principle. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a structural diagram of the moraine dam model.

[0027] Figure 2 The figure is a schematic diagram showing the relationship between the predicted values ​​of the prediction model disclosed in the second prior art, the predicted values ​​of the prediction model provided by the present invention, and the experimental measured values. DETAILED DESCRIPTION

[0028] The above contents of the present invention are further described in detail below in conjunction with the specific implementation methods of the embodiments. However, this should not be understood as the scope of the above subject matter of the present invention being limited to the following examples. Various substitutions or changes made according to common technical knowledge and customary means in the art without departing from the above technical ideas of the present invention should be included in the scope of the present invention.

[0029] Embodiment 1:

[0030] Based on years of project research experience, the team members keenly discovered that the presence of buried ice inside the dam will change the conditions for the dam to burst, and decided to conduct an experimental study on the impact of buried ice melting on the overtopping and bursting process of moraine dams. Through experiments, it was found that the presence of buried ice will have a significant impact on the bursting process of moraine dams: buried ice will affect the bursting process by affecting the internal structure of the dam, thereby changing the bursting peak flow. After a series of theoretical analysis and experimental verification, a scientific and effective method for predicting the peak flow of moraine dam bursting that takes into account the influence of buried ice was finally formed.

[0031] First, the moraine dam burst peak flow prediction method provided in this embodiment uses ice content, ice melting degree, and ice particle size as buried ice parameters for the first time to characterize the influence of buried ice on the moraine dam burst peak flow, and adds them into control variables for studying the changes in the moraine dam burst peak flow.

[0032] Secondly, the method for predicting the peak flow rate of moraine dam burst provided in this embodiment obtains the adjustment coefficient and amplification coefficient that characterize the influence of ice content, ice melting degree, and ice particle size on the peak flow rate of moraine dam burst through simulation experiments; and quantitatively analyzes the influence of buried ice parameters on the change of the peak flow rate of moraine dam burst.

[0033] Finally, the moraine dam burst peak flow prediction method provided in this embodiment provides a moraine dam burst peak flow prediction model that takes into account the influence of buried ice. The peak flow prediction of the moraine dam burst containing ice can be performed by inputting the conventional monitoring data of the existing dam body monitoring data center, with high prediction accuracy and fast speed.

[0034] In summary, this embodiment provides a method for predicting the peak flow rate of moraine dam burst considering the influence of buried ice, and uses ice content, ice melting degree, and ice particle size as buried ice parameters that characterize the influence of buried ice on the peak flow rate of moraine dam burst. Through simulation experiments, adjustment coefficients and amplification coefficients that characterize the influence of ice content, ice melting degree, and ice particle size on the peak flow rate of moraine dam burst are obtained; then, the adjustment coefficients and amplification coefficients are brought into the moraine dam burst peak flow prediction model to predict the peak flow rate of moraine dam burst.

[0035] Embodiment 2:

[0036] Based on the research results disclosed in the prior art and the technical ideas proposed in Example 1, this embodiment proposes a moraine dam breach peak flow prediction model that takes into account the influence of buried ice.

[0037] Prior art 1: Costa, John E. and Schuster, Robert L. in 1987 obtained a prediction formula between the outburst peak flow and the potential energy of moraine lake water based on statistical analysis of 6 actual case data.

[0038] The specific formula is as follows:

[0039]

[0040] Where: Q p is the peak flow rate of the dam body, in m 3 / s;

[0041] P E is the glacial lake potential energy, PE =H d ·V·c W , unit J;

[0042] H d is the height of the dam, in m;

[0043] V is the storage capacity of moraine lake, unit: m 3 ;

[0044] c W is the density of water, take 9.8 KN / m 3 .

[0045] The prediction formula provided by the prior art 1 has a small number of design cases and only considers the impact of dam height and reservoir capacity on peak burst flow. There are few parameters and the left and right dimensions of the equation are not harmonious. Most importantly, the prediction formula does not consider the impact of dam structure, dam material composition and internal buried ice, which has great limitations in practical application.

[0046] Prior art 2: In 2011, Peng Ming and Zhang Limin established a full parameter model and a simplified model for estimating the peak flow of landslide dam breach through dimensionless method and regression analysis method based on a compiled landslide dam actual case database.

[0047] The specific formula is as follows:

[0048] Full variable model:

[0049]

[0050] Simplified model:

[0051]

[0052] Where: Q p is the peak flow rate of the dam body, in m 3 / s;

[0053] g is the gravitational acceleration, which represents the dynamic characteristics of water flow and is taken as 9.18 g / cm 3 ;

[0054] H d is the height of the dam, in m;

[0055] H r = 1 m, which represents unit length and has no actual physical meaning;

[0056] W d is the width of the dam, in m;

[0057] V d is the volume of the dam, in m 3 ;

[0058] V l is the storage capacity behind the dam, unit: m 3 ;

[0059] e’ is the porosity of the dam body;

[0060] a It is a parameter related to the erosivity of the dam body. When the dam body is highly erosible, it is 1.276; when it is moderately erosible, it is -0.336; when it is low erosible, it is -1.532.

[0061] The model provided by the second prior art is mainly applicable to landslide dams, and does not take into account the differences in the geometric shape and material composition of moraine dams, nor the impact of buried ice on burst flow. It cannot be directly applied to moraine dams, especially moraine dams containing buried ice.

[0062] In this embodiment, based on the existing model results, indoor model experiments were carried out. Based on real and effective experimental data, the influence of buried ice content, buried ice particle size and melting was considered on the basis of predecessors. Dimensional analysis and regression analysis were used as analysis methods to construct a function expression and prediction model for the peak flow of moraine dam burst considering the influence of buried ice.

[0063] The functional expression of the peak discharge of moraine dam burst considering the influence of buried ice is as follows:

[0064] (Formula 1)

[0065] Where: Q p is the peak flow rate of the dam body, in m 3 / s;

[0066] H d is the height of the dam, in m;

[0067] L d is the bottom length of the dam, in m;

[0068] g is the gravitational acceleration, which represents the dynamic characteristics of water flow and is taken as 9.18 g / cm 3 ;

[0069] V i is the volume fraction of buried ice, used to reflect the ice content, expressed as a percentage; V i =( V ice / V dam )×100%, where: V ice Refers to the volume of buried ice inside the dam body, usually measured by geophysical exploration technology; V dam Refers to the total volume of the dam body, usually calculated by measuring relevant geometric parameters on site;

[0070] a i is the average particle size of buried ice, in mm; its value is generally a known quantity in experiments, and can be approximately determined in the field by excavation or ice core sampling, or by averaging the particle size data obtained by ice core sampling and excavation;

[0071] d 50 The median particle size of the dam body particles is used to characterize the dam body structure and material characteristics, in mm;

[0072] d max It is the maximum particle size of the dam body particles, used to characterize the dam body structure and material characteristics, unit: mm;

[0073] e’ is the porosity ratio of the dam body, which is usually calculated through the basic indicators of the soil:

[0074] ,

[0075] in: G s is the specific gravity of soil, r w is the density of water, which is 1.0 g / cm at room temperature. 3 , r d is the dry density of soil.

[0076] The prediction formula for the peak flow of moraine dam burst considering the influence of buried ice is as follows:

[0077]

[0078] Where: Q p * The maximum peak flow rate under ice melting conditions, in m 3 / s;

[0079] Q p is the peak flow rate of the dam body, in m 3 / s;

[0080] or is the magnification factor, or ≥1;

[0081] g is the gravitational acceleration, which represents the dynamic characteristics of water flow and is taken as 9.18 g / cm 3 ;

[0082] H d is the height of the dam, in m;

[0083] L d is the bottom length of the dam, in m;

[0084] V i is the volume fraction of buried ice;

[0085] a i is the average particle size of buried ice, in mm;

[0086] d 50 is the median particle size of the dam particles, in mm;

[0087] d max is the maximum particle size of the dam body particles, in mm;

[0088] e’ is the porosity ratio of the dam body;

[0089] k、b、c、d、m These are adjustment factors.

[0090] The other parts of this embodiment are the same as those of Embodiment 1, and thus will not be described in detail.

[0091] Embodiment 3:

[0092] This example describes the experimental process in detail based on Example 1 or Example 2.

[0093] Through indoor model experiments, moraine dam breach experiments were carried out with dam height, gradation, ice content, ice melting and ice particle size as variables to explore the influence of the above variables on the peak breach flow.

[0094] 1. Experimental setup

[0095] The experimental device used in the simulation experiment mainly consists of a water supply device, a water collection tank, a water trough, a waste pool and a moraine dam model.

[0096] The dimensions of the water supply device are 1.5 m long × 1.5 m wide × 1.0 m high, and the upstream water flow rate can be adjusted. The water trough is 6.0 m long × 0.5 m wide × 0.5 m high, and the slope of the water trough is set to 1° to simulate the natural river channel. At least one side of the water trough side wall is made of fully transparent tempered glass. The waste pool is 1.0 m long × 1.0 m wide × 0.45 m high and is used to recycle waste. The space between the dam body and the water collection tank will serve as the upstream reservoir area. In order to make the bottom of the dam body in good contact with the bottom of the water trough, a moving bed is set in the water trough to avoid problems such as boundary seepage caused by direct contact between soil particles and smooth boundaries.

[0097] 2. Moraine Dam Model

[0098] The structure of the moraine dam model is as follows: Figure 1 As shown, it is piled in the water tank. The design parameters of the experimental conditions are shown in Table 1:

[0099] Table 1 Experimental conditions design parameters

[0100]

[0101] By collecting case information of moraine dams that have collapsed in Tibet, the geometric range of the moraine dam model was summarized and scaled down according to a geometric scale of 1:250. The variable range of this experimental design is within the actual scale range, and the setting of the model experiment is reasonable.

[0102] In the laboratory, moraine dam models are generally made of loose moraine soil with poor gradation, which contains less sticky particles and more coarse particles. This example refers to the actual composition of the moraine dam and configures the dam body materials based on the particle gradation of the Midui Guangxiecuo moraine dam. The maximum particle size of the dam body particles obtained is 2 cm, and the natural density is r =1800 kg / m 3 , initial porosity ratio e 0 = 0.341.

[0103] The distribution of buried ice in the solid dam body is highly random and spatially non-uniform. The shape and particle size of the buried ice are also non-uniform. Geophysical detection methods can be used to obtain the ice content and distribution location of buried ice within a certain depth range of the moraine dam entity. The ice blocks used in the experiment were frozen and prepared using cube molds of different sizes, and the range of ice particle size parameters was wide. At the same time, the ice blocks were randomly distributed in the dam body, and a wide range of ice contents were configured for several experiments to obtain a large amount of experimental data.

[0104] 3. Experimental Equipment

[0105] The experimental equipment used in the simulation experiment includes a camera, a water pressure sensor and a data acquisition instrument.

[0106] The camera is used to record the entire experimental process, such as a digital high-definition camera SONY FDR-AX60, 4,096 × 2,160 pixels, 50 fps. The water pressure sensor is used to record the water level upstream of the dam. The data acquisition instrument is used to collect data collected by the water pressure sensor to facilitate the subsequent calculation of the flow at the breach.

[0107] 4. Experimental Environment

[0108] The experiment was conducted at the Dongchuan Debris Flow Observation Station of the Chinese Academy of Sciences. Before the dam was built, the prepared ice was placed in an insulated box in a low-temperature environment to ensure that the ice was still frozen when the building began. The ambient temperature at the beginning of the experiment was 20°C, and the ice was exposed to the air for a short time, so the melting of the ice caused by the temperature could be ignored.

[0109] 5. Experimental process

[0110] The experimental steps are as follows:

[0111] Step 1: Adjust the incoming flow according to the right-angle weir flow formula;

[0112] Step 2: Determine the geometric dimensions of the dam body, configure the dam body materials according to the grading information of the experimental plan; determine the particle size and content of the ice used; determine the location of the dam body;

[0113] Step 3: Pile up the dam body and evenly lay it in layers inside the dam body;

[0114] Step 4: Start timing after the stacking is completed, and the start timing is the zero point of ice melting timing;

[0115] Step 5: Turn on the water pressure sensor and data acquisition instrument, mark the water pressure sensor at zero, then start to store water and collect water pressure data of the upstream reservoir area. The collection time interval is 1s, and the collection stops when the dam body fails.

[0116] Step 6: Calculate the flow rate at the breach according to the flow balance formula. The maximum value in the flow curve at the breach is the peak burst flow rate. The peak burst flow rates obtained under different working conditions are different.

[0117] Flow balance formula: inflow per unit time + change in reservoir water volume per unit time = flow discharged through the breach per unit time; among them, the change in reservoir water volume per unit time is negative if it increases and positive if it decreases.

[0118] 6. Experimental Results

[0119] After repeating the above content with multiple groups of experiments, multiple discoveries were made.

[0120] (1) Peak flow of dam body Q p Length of dam body bottom L d Impact, at the height of the dam H d When the dam bottom length is constant, L d The longer it is, the smaller the slope of the dam body, the larger the volume of the dam body, and the smaller the peak burst flow.

[0121] (2) Peak flow of dam failure Q p The maximum particle size of the dam material to be characterized d max Influence, the maximum particle size of the dam particles d max Increase and decrease.

[0122] (3) Peak flow of dam body Q p Porosity of dam body e ’ Porosity of dam body e ’ It represents the looseness of the dam material. The larger the porosity, the looser the dam material and the weaker the material's anti-erosion ability, thus affecting the peak burst flow.

[0123] (4) Peak flow of dam burst Q p Dam body height H d Influence, with the height of the dam H d Increase and grow.

[0124] (5) Peak flow of dam burst Q p The median particle size of the dam particles affected by the gradation parameters d 50 Influence, along with the median particle size of the dam body particles d 50 Increase and decrease.

[0125] (6) Peak flow of dam burst Q p Volume fraction of buried ice characterized by ice content V i The effect varies with the volume fraction of buried ice. V i Increase and grow.

[0126] (7) Peak dam burst flow Q p Affected by the degree of ice melting, it shows a trend of first increasing and then decreasing.

[0127] (8) Peak dam burst flow Q p Average particle size of buried ice characterized by ice particle size a i The influence of the average particle size of buried ice a i Increase and decrease.

[0128] Among the above findings, the first four points are the same as the results of previous studies, and the last four points are new research results.

[0129] Based on the above research results, this embodiment selects the dam height H d , dam bottom length L d , Gravitational acceleration g , Volume fraction of buried ice V i , the average particle size of buried ice a i , median particle size of dam particles d 50 , the maximum particle size of the dam body particles d max , dam body porosity ratio e ’ As the peak flow rate affecting the dam body Q p The key parameters of the function expression are as follows:

[0130] (Formula 1)

[0131] That is, the functional expression of the peak discharge of moraine dam outburst considering the influence of buried ice.

[0132] After clarifying the dependent variable and its control variables, select g , H d and d max As a unit, according to the dimensional analysis method, the following dimensionless function relationship can be obtained:

[0133] (Formula 2)

[0134] The next step is to construct an empirical relationship through multiple regression.

[0135] This embodiment adopts a regression formula in the form of a nonlinear combination, that is, constructs a dimensionless relationship in the form of a product, as follows:

[0136] (Formula 3)

[0137] In the formula, Y is the dependent variable, X 1. X 2… X i is the independent variable, and the subscript i is the total number of independent variables; a 0 and a 1. a 2… a i is the regression coefficient.

[0138] The multivariate regression analysis in product form is used to establish the following prediction formula:

[0139] (Formula 4)

[0140] In the formula, k、b、c、d、m These are adjustment factors.

[0141] The Levenberg-Marquardt algorithm is used to perform nonlinear fitting on the experimental results to obtain the values ​​of each adjustment coefficient, as shown in Table 2:

[0142] Table 2 Values ​​of adjustment coefficients

[0143]

[0144] Will k =0.032, b =5.064, c =0.077, d = -0.255, m =6.274Substitute into formula 4 and we get the peak flow rate of the dam body. Q p The expression is:

[0145] (Formula 5)

[0146] It is worth noting that the expression of Formula 5 does not take into account the variable of ice melting degree. For this reason, the following supplement is made: the peak flow rate caused by the melting of buried ice shows a trend of first increasing and then decreasing. According to experimental observation, when the ice melting degree is 80%, it is the most dangerous time for the dam to burst. Therefore, this embodiment further defines the amplification factor or , used to express the ratio of the maximum peak burst flow when the buried ice melts and the peak burst flow when the buried ice does not melt under the same working conditions.

[0147] Amplification factor or Height to dam H d and coarse particle content of the dam body C s Related, using the median particle size of the dam particles d 50 Represents the influence of different coarse particle contents, and the amplification coefficient is obtained by regression analysis fitting or The empirical expression is as follows:

[0148] (Formula 6)

[0149] Further calculation of the peak outburst flow in the case of ice melting Q p *:

[0150] (Formula 7)

[0151] Thus, the moraine dam burst peak flow prediction model considering the influence of buried ice provided by the present invention is obtained. Through this prediction model, the burst peak flow when the ice in the moraine dam is not melted and the maximum burst peak flow when the ice in the moraine dam is melted can be quantitatively predicted.

[0152] It should be noted that the magnification factor or ≥1, indicating that the maximum peak flow rate when the buried ice in the moraine dam melts is greater than the corresponding peak flow rate when the buried ice does not melt, and the damage caused by the moraine dam once it breaks is also more serious. Therefore, the disaster warning system needs to obtain the peak flow rate when the buried ice does not melt, which is used as an important reference data for calculating the warning threshold, and then judge the urgency of the moraine dam's possible collapse; at the same time, the disaster warning system also needs to obtain the maximum peak flow rate when the buried ice melts, which is used to evaluate the hazard level when the moraine dam breaks, and provide an important reference for designing downstream prevention and control projects or emergency plans when disasters occur.

[0153] Based on the above simulation experiment, the predicted values ​​obtained by the prediction model provided by the present invention, the predicted values ​​obtained by the prediction model disclosed in the prior art 2, and the actual measured values ​​of the experiment are compared and analyzed. The results are as follows: Figure 2 As shown, it can be seen that the predicted value obtained by the prediction model provided by the present invention is closer to the measured value. Therefore, it is proved that the moraine dam burst peak flow prediction model considering the influence of buried ice provided by the present invention has better prediction accuracy.

[0154] Based on the above moraine dam burst peak flow prediction model considering the influence of buried ice, this embodiment provides a moraine dam burst peak flow prediction method that considers the ice content, ice melting degree, and ice particle size of buried ice. This method can predict the burst peak flow under ice melting conditions based on basic data obtained from field surveys, thereby guiding disaster prevention and control and providing an effective reference for emergency response measures.

[0155] The other parts of this embodiment are the same as those of Embodiment 1 or Embodiment 2, and thus will not be described in detail.

[0156] Embodiment 4:

[0157] The moraine dam burst peak flow prediction model considering the influence of buried ice obtained based on any one of Examples 1 to 3 can be used to obtain the burst peak flow of the dam body. Q p The peak flow rate of moraine dam can be predicted by the value of Q P * The value of is used to predict the peak burst flow when the buried ice in the dam melts.

[0158] First, conduct on-site surveys to obtain basic survey parameters. The basic survey parameters include the height of the moraine dam. H d , dam bottom length L d , median particle size of dam particles d 50 , the maximum particle size of the dam body particles d max , Volume fraction of buried ice V i and the average particle size of buried ice a i .

[0159] Height of moraine dam H d , dam bottom length L d It can be measured on-site using a rangefinder, or extracted through remote sensing data, etc.

[0160] Median particle size of dam particles d 50 and the maximum particle size of the dam particles d max It can be determined through sampling, drying, screening tests, etc.

[0161] Volume fraction of buried ice V iIt can be obtained by using relevant geophysical exploration technology, such as electrical resistivity tomography (ERT) (Thompson et al., 2017), which can invert the content of buried ice in the dam body by using the different characteristic resistivity values ​​of different materials. V i Other methods include but are not limited to the gas expansion method, the improved thermal pulse method, and high-precision fiber optic sensing technology (Wu et al., 2021).

[0162] Average particle size of buried ice a i It can be determined approximately by field excavation or ice core sampling. The average value is obtained by sampling and excavating the particle size data. In addition, if it is under experimental conditions, this value is generally a known quantity.

[0163] Porosity ratio of dam e ’ , calculated through the basic indicators of soil:

[0164] ,

[0165] in: G s is the specific gravity of soil, r w is the density of water, which is 1.0 g / cm at room temperature. 3 , r d is the dry density of soil.

[0166] Then the above parameters are processed to obtain dimensionless quantities L d / H d and( a i × d 50 ) / ( d max 2 ) value, and then L d / H d , V i 、( a i × d 50 ) / ( d max 2 )and e ’ Substituting into formula 5, we can calculate the peak flow rate of the dam body: Qp .

[0167] To determine the peak outburst flow in the event of melting of buried ice, first H d and d 50 The amplification factor is determined by Equation 6 or , then substitute into equation 7 to obtain the peak flow rate under ice melting conditions Q P * , thereby determining the peak burst flow when the buried ice in the dam body melts. The determination of this value can determine the most dangerous situation of ice-containing moraine dam burst, which is conducive to the effective deployment and implementation of corresponding prevention and control measures.

[0168] The other parts of this embodiment are the same as any one of Embodiments 1 to 3, and thus will not be described in detail.

[0169] Embodiment 5:

[0170] This embodiment simplifies a case based on the statistics of glacial lake outbursts in the Dizang area, and explains in detail the prediction method proposed in the present invention based on any one of Embodiments 1 to 4.

[0171] Firstly, the geometric parameters of the dam body are determined, the particle grading information and the porosity ratio information of the dam body material are obtained, and the ice content and ice particle size inside the dam body are obtained.

[0172] Get the height of the dam H d 35 m, the crest length is 10 m, and the upstream slope is β The downstream slope is 35°. α is 30°, so the bottom length of the dam is L d = 10 + H d / tan β + H d / tan a =113.47 m.

[0173] The gradation curve is obtained through field survey sampling: sampling-drying-screening test-gradation curve, and the median particle size of the dam body particles is extracted through the gradation curve d 50 and the maximum particle size of the dam particles d max 4.23 mm and 80 mm respectively; and the initial porosity ratio of the dam material was determined e 0 is 0.383.

[0174] Get the volume fraction of buried ice Vi The average particle size of buried ice is 25%. a i is 35 mm.

[0175] In addition, the acceleration due to gravity g Take 9.18 g / cm 3 .

[0176] The above parameters are sorted out to get:

[0177] L d / H d = 113.47 / 45 = 3.242;

[0178] ( a i × d 50 ) / ( d max 2 )=(35*4.23) / (80*80)=0.023.

[0179] Then, the obtained L d / H d , V i 、( a i × d 50 ) / ( d max 2 )and e ’ Substitute into equation 5:

[0180]

[0181] = [0.032 × 3.242 5.064 ×0.25 0.077 ×0.023 -0.255 ×0.363 6.274 ]×9.18 1 / 2 ×45 5 / 2

[0182] =1142.73 m 3 / s.

[0183] Furthermore, when considering the effect of buried ice melting, the amplification factor is first calculated according to Equation 6: or ;

[0184] OR=1.142×( H d ) 0.142 ×( d 50 ) 0.098 =1.142×35 0.142 ×4.23 0.098 =1.571.

[0185] Then the peak flow of the dam body calculated above is Q p and magnification factor or Substitute into equation 7:

[0186]

[0187] =1.571×1142.73 = 1795.229 m 3 / s;

[0188] Finally, the peak flow rate under ice melting is obtained. Q p *.

[0189] The other parts of this embodiment are the same as any one of Embodiments 1 to 4, and thus will not be described in detail.

[0190] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification or equivalent change made to the above embodiment according to the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for predicting peak flow of moraine dam breach considering the influence of buried ice, characterized in that: The ice content, ice melting degree and ice particle size are used as buried ice parameters to characterize the influence of buried ice on the peak flow of moraine dam burst. Through simulation experiments, the adjustment coefficient and amplification coefficient are obtained to characterize the influence of ice content, ice melting degree and ice particle size on the peak flow of moraine dam burst. Then, the adjustment coefficient and amplification coefficient are brought into the moraine dam burst peak flow prediction model to predict the peak flow of moraine dam burst. The prediction formula for the peak flow of moraine dam burst considering the influence of buried ice is as follows: Where: Q p * The maximum peak flow rate under ice melting conditions, in m 3 / s; Q p is the peak flow rate of the dam body, in m 3 / s; η is the magnification factor, η ≥1; g is the gravitational acceleration, which represents the dynamic characteristics of water flow and is taken as 9.18 g / cm 3 ; H d is the height of the dam, in m; L d is the bottom length of the dam, in m; V i is the volume fraction of buried ice; a i is the average particle size of buried ice, in mm; d 50 is the median particle size of the dam particles, in mm; d max is the maximum particle size of the dam body particles, in mm; e’ is the porosity ratio of the dam body; k, b, c, d, m Both are adjustment factors.

2. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The ice content is characterized by the volume fraction of buried ice; wherein the volume fraction of buried ice is the percentage of the volume of buried ice inside the dam body to the total volume of the dam body.

3. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The ice particle size is characterized by the average particle size of buried ice.

4. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The amplification factor is used to characterize the ratio of the maximum peak burst flow when the ice melts to the peak burst flow when the ice does not melt under the same working conditions; the value of the amplification factor is calculated based on the dam body height and the coarse particle content of the dam body.

5. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 4, characterized in that: The coarse particle content of the dam body is characterized by the median particle size of the dam body particles.

6. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The method for obtaining the adjustment coefficient is specifically: Firstly, a series of miniature models were built to simulate the actual moraine dam to simulate the moraine dam breach state and obtain the peak breach flow. The values ​​of the buried ice parameters inside the dam bodies of each miniature model are not exactly the same. Then, the dam height, dam bottom length, gravitational acceleration, ice content, ice particle size, median particle size of dam particles, maximum particle size of dam particles, and dam porosity ratio are used as variables for simulating the breach state of moraine dam, and a prediction expression for the breach peak flow is obtained based on the dimensional analysis method and the multivariate regression analysis method; the prediction expression for the breach peak flow is composed of the variables for simulating the breach state of moraine dam and the adjustment coefficient; Finally, simulation experiments are carried out on a series of miniature models to obtain experimental data consisting of multiple groups of variable values ​​with different numerical values, and the value of the adjustment coefficient is obtained through a fitting algorithm.

7. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 6, characterized in that: According to the experimental data obtained from the simulation experiment, the Levenberg-Marquardt algorithm is used for nonlinear fitting to obtain the value of the adjustment coefficient.

8. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The experimental device used in the simulation experiment includes a water supply device, a water collection tank, a water tank, a waste pool and a moraine dam model; the water tank is provided with a moving bed to avoid boundary seepage caused by direct contact between soil particles and smooth boundaries.

9. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 8, characterized in that: The raw materials of the moraine dam model include moraine soil and ice blocks; The method for making the moraine dam model is: ice blocks in a frozen state are randomly distributed in loose moraine soil and piled up to form the moraine dam model.

10. The method for predicting peak flow of moraine dam breach considering the influence of buried ice according to claim 1, characterized in that: The experimental equipment used in the simulation experiment includes a camera, a water pressure sensor and a data acquisition instrument.

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