A method and a terminal device for calculating debris flow parameters

Abstract

A method and a terminal device for calculating debris flow parameters, which relate to the field of debris flow disaster prevention and control. In this method, horizontal coordinate data of a target cross-section on the debris flow path and elevation data corresponding to the horizontal coordinate data are obtained to generate geometric feature data; a terrain fitting function corresponding to the target cross-section is fitted through the geometric feature data; a cross-sectional area function and a wetted perimeter function are generated through the terrain fitting function and the deepest mud level; the cross-sectional area function and the wetted perimeter function are substituted into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level. Implementing the technical solution provided by this application achieves the effect of improving the reliability of the calculated debris flow parameters.

Description

Technical Field

[0001] This application relates to the field of debris flow disaster prevention and control, and specifically relates to a method and a terminal device for calculating debris flow parameters. Background Art

[0002] Under the interaction of the complex and changeable natural environment and the increasingly frequent human activities, the prevention and control of natural disasters have become an important global issue. Among them, debris flow, as a natural disaster unique to mountainous areas, has strong suddenness and great destructive power, which not only seriously threatens the safety of mountain residents, but also causes huge damage to economic construction and the ecological environment.

[0003] To avoid the damage caused by debris flow, researchers will construct corresponding physical models according to the actual terrain and material composition of the debris flow occurrence area, then simulate the movement process of the debris flow based on the constructed physical model, and then use various measurement devices and technical means to obtain key parameters such as the flow velocity, flow rate, and impact force of the debris flow. However, this method is easily affected by the accuracy of the physical model, the control of experimental conditions, etc., resulting in low reliability of the obtained debris flow parameters. Or, estimate the debris flow parameters through the morphological analysis method. Among them, the morphological analysis method is to first examine the topographic and geomorphic features of the debris flow occurrence area, including the slope of the mountain body, the shape of the gully, the longitudinal slope drop of the gully bed, etc., then analyze the characteristic results of the topographic and geomorphic features, and then use empirical formulas or theoretical models to estimate the debris flow parameters, and then compare the estimated parameters with the actual observed data for verification to ensure its accuracy and reliability. However, the accuracy of this method depends to a large extent on the applicability of the empirical formula and the theoretical model, so there may be certain errors under different geological and environmental conditions.

[0004] Therefore, how to improve the reliability of the calculated debris flow parameters has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides a method and a terminal device for calculating debris flow parameters, which can improve the reliability of the calculated debris flow parameters.

[0006] In a first aspect, this application provides a method for calculating debris flow parameters, including: obtaining the horizontal coordinate data of a target cross-section on the debris flow path and the elevation data corresponding to the horizontal coordinate data, and generating geometric feature data; fitting a terrain fitting function corresponding to the target cross-section through the geometric feature data; generating a cross-sectional area function and a wetted perimeter function through the terrain fitting function and the deepest mud level; substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level.

[0007] By adopting the above technical solution, by obtaining the horizontal coordinate data and elevation data of the target cross-section on the debris flow path, fitting the terrain fitting function to ensure the accuracy and integrity of the terrain information, and then using the relationship between the terrain fitting function and the cross-sectional area and wetted perimeter length, taking the deepest mud level as an unknown parameter, deriving the cross-sectional area function and wetted perimeter length function about the deepest mud level, and integrating these functions into the Manning formula, the relatively accurate deepest mud level can be calculated, which is convenient for researchers to further study the debris flow.

[0008] Optionally, fitting the terrain fitting function corresponding to the target cross-section through geometric feature data includes: constructing a cubic polynomial S(x), where the cubic polynomial satisfies S(xi) = f(xi), S'(xi) = f'(xi), S”(xi) = f”(xi), f(x) is the terrain function of the target cross-section, and xi is the horizontal coordinate data; substituting the geometric feature data into the cubic polynomial S(x) to calculate the terrain fitting function.

[0009] By adopting the above technical solution, by ensuring that S(xi), S'(xi) and S”(xi) are respectively equal to f(xi), f'(xi) and f”(xi), the accuracy of the terrain fitting function at the data points can be guaranteed, and at the same time, the consistency of the first derivative and the second derivative of the terrain fitting function is ensured, thereby improving the smoothness and continuity of the terrain fitting function.

[0010] Optionally, before calculating the terrain fitting function from the geometric feature data, the method further includes: dividing the horizontal coordinate data into multiple intervals; substituting the partial geometric feature data corresponding to each interval in the multiple intervals into the cubic polynomial S(x), and calculating the terrain fitting function by the spline interpolation method, and the terrain fitting function includes multiple cubic polynomials S(x).

[0011] By adopting the above technical solution, by dividing the horizontal coordinate data into multiple intervals and calculating the terrain fitting function of each interval respectively, the terrain change of the target cross-section can be described more accurately, the accuracy and reliability of the terrain fitting are improved, and it is helpful to calculate the debris flow related parameters more accurately.

[0012] Optionally, the cross-sectional area function is The wetted perimeter length function is h is the deepest mud level, a(h) is the left intersection point of the terrain fitting function and the deepest mud level line, and b(h) is the right intersection point of the terrain fitting function and the deepest mud level line.

[0013] By adopting the above technical solution, by calculating the cross-sectional area and wetted perimeter length through integration, the complex contour of the irregular gully cross-section can be accurately adapted, ensuring the accuracy of the calculation result and avoiding the error caused by simple approximation.

[0014] Optionally, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thus obtaining the deepest mud level, the method further includes: substituting the deepest mud level into the cross-sectional area function and the wetted perimeter function to obtain the cross-sectional area and the wetted perimeter; and obtaining the hydraulic radius based on the cross-sectional area and the wetted perimeter.

[0015] By adopting the above technical solution, more accurate cross-sectional area and wetted perimeter can be obtained based on the deepest mud level, so as to calculate a more reliable hydraulic radius, providing a scientific basis for evaluating the hydrodynamic behavior of debris flows, risk prediction and prevention measure design.

[0016] Optionally, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thus obtaining the deepest mud level, the method further includes: substituting the deepest mud level into the cross-sectional area function to obtain the cross-sectional area of the target cross-section; and obtaining the debris flow velocity based on the cross-sectional area.

[0017] By adopting the above technical solution, calculating the debris flow velocity based on the cross-sectional area provides highly accurate relevant parameters for disaster assessment, greatly enhancing the timeliness and accuracy of debris flow monitoring and risk prevention and control.

[0018] Optionally, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thus obtaining the deepest mud level, the method further includes: comparing the deepest mud level, the hydraulic radius and the debris flow velocity with the preset deepest mud level, the preset hydraulic radius and the preset debris flow velocity respectively to obtain the differences in the deepest mud level, the hydraulic radius and the flow velocity; and determining the risk level based on the differences in the deepest mud level, the hydraulic radius and the flow velocity.

[0019] By adopting the above technical solution, by obtaining the characteristic parameters related to debris flows and calculating the parameter differences, it is possible to provide a scientific basis for debris flow disaster warning and risk control, enhance the pertinence and timeliness of preventive measures, and thus effectively improve the regional safety guarantee ability and emergency response efficiency.

[0020] In a second aspect of the present application, a terminal device is provided, including: a first generation module for obtaining the horizontal coordinate data of a target cross-section on the debris flow path and the elevation data corresponding to the horizontal coordinate data, and generating geometric feature data; a fitting module for fitting the terrain fitting function corresponding to the target cross-section through the geometric feature data; a second generation module for generating a cross-sectional area function and a wetted perimeter function through the terrain fitting function and the deepest mud level; and an obtaining module for substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thus obtaining the deepest mud level.

[0021] In a third aspect of the present application, an electronic device is provided, including a processor (501), a memory (505), a user interface (503), and a network interface (504). The memory (505) is used to store instructions, the user interface (503) and the network interface (504) are used to communicate with other devices, and the processor (501) is used to execute the instructions stored in the memory (505) so that the electronic device (500) executes the method according to any one of the first aspects.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions, and when the instructions are executed, the method steps according to any one of the first aspects are executed.

[0023] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0024] 1. By fitting a terrain fitting function and dividing the horizontal coordinate data into multiple intervals, the accuracy and integrity of the terrain information can be ensured. Then, using the relationship between the terrain fitting function and the cross-sectional area and wetted perimeter length, with the deepest mud level as an unknown parameter, the cross-sectional area function and wetted perimeter length function regarding the deepest mud level are derived, so that a relatively accurate deepest mud level can be calculated.

[0025] 2. By obtaining the characteristic parameters related to debris flow and calculating the parameter differences, a scientific basis can be provided for debris flow disaster warning and risk control, enhancing the pertinence and timeliness of preventive measures, and thus effectively improving the regional safety guarantee ability and emergency response efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flowchart of the method for calculating debris flow parameters disclosed in the embodiments of the present application.

[0027] Figure 2 is the original target cross-section contour line exemplified in the embodiments of the present application.

[0028] Figure 3 is the target cross-section spline interpolation fitting contour exemplified in the embodiments of the present application.

[0029] Figure 4 is a schematic structural diagram of a terminal device disclosed in the embodiments of the present application.

[0030] Figure 5 is a schematic structural diagram of an electronic device disclosed in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments.

[0032] In the description of the embodiments of this application, words such as "for example" or "for illustration" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "for example" or "for illustration" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, using words such as "for example" or "for illustration" is intended to present relevant concepts in a specific way.

[0033] In the description of the embodiments of this application, the meaning of the term "a plurality of" refers to two or more. For example, a plurality of systems refers to two or more systems, and a plurality of screen terminals refers to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the technical features indicated. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. The terms "include", "comprise", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0034] The following Figure 1 will give a detailed description of a method for calculating debris flow parameters provided by the embodiments of this application.

[0035] Step S101: The terminal device acquires the horizontal coordinate data of the target cross-section on the debris flow path and the elevation data corresponding to the horizontal coordinate data, and generates geometric feature data.

[0036] The target cross-section refers to a cross-section located on the debris flow path. Optionally, the target cross-section is a cross-section on the debris flow path selected by researchers with representativeness and monitoring convenience.

[0037] The horizontal coordinate data can be understood as the horizontal coordinates corresponding to multiple points on the target cross-section. The elevation data is data including the elevation values corresponding to each horizontal coordinate in the horizontal coordinate data. In the embodiments of this application, the actual contour of the target cross-section can be constructed through the horizontal coordinate data and the elevation data.

[0038] The geometric feature data is data including the horizontal coordinate data and the elevation data.

[0039] Exemplarily, the terminal device conducts on-site measurements of the target cross-section on the debris flow path through a GPS device or a total station. The horizontal coordinates of each measurement point are recorded through the GPS device, and the vertical distance (elevation) from the reference point is measured by the total station. For example, ten points are selected at different positions of the target cross-section, and their horizontal coordinates and elevations are recorded. The obtained geometric feature data {(x i ,y i )∣x∈R, y∈R} is (1242, -1000), (1155, -50), (1269, 0.00), (1069, 7.16), (1068, 15.90), (1062, 22.94), (1063, 43.93), (1063, 49.65), (1065, 53.10), (1067, 84.62), (1068, 131.40), (1071, 151.90), (1099, 200.00).

[0040] Step S102: The terminal device fits the terrain fitting function corresponding to the target cross-section through the geometric feature data.

[0041] The terrain fitting function can be understood as a function used to describe the height change of the terrain of the target cross-section, and it can determine the elevation value at the horizontal coordinate according to the substituted horizontal coordinate.

[0042] In an optional implementation manner, fitting the terrain fitting function corresponding to the target cross-section through the geometric feature data includes: constructing a cubic polynomial S(x), and the cubic polynomial satisfies S(xi) = f(xi), S'(xi) = f'(xi), S”(xi) = f”(xi), where f(x) is the terrain function of the target cross-section and xi is the horizontal coordinate data; substituting the geometric feature data into the cubic polynomial S(x) to calculate the terrain fitting function.

[0043] Combined with the above example, the terrain function of the target cross-section is y = f(x), and a cubic polynomial S(x) = ax 3 +bx 2 +cx + d is constructed. For each data point (x i ,y i ) in the geometric feature data, there is a system of equations Then substitute the geometric feature data into the system of equations for solution to obtain the terrain fitting function.

[0044] In this embodiment, by ensuring that S(xi), S'(xi), and S''(xi) are equal to f(xi), f'(xi), and f''(xi) respectively, the accuracy of the terrain fitting function at the data points can be guaranteed, and at the same time, the consistency of the first derivative and the second derivative of the terrain fitting function is ensured, thereby improving the smoothness and continuity of the terrain fitting function.

[0045] In an alternative embodiment, before calculating the terrain fitting function from the geometric feature data, the method further includes: dividing the horizontal coordinate data into multiple intervals; substituting the partial geometric feature data corresponding to each interval of the multiple intervals into the cubic polynomial S(x), and calculating the terrain fitting function through spline interpolation. The terrain fitting function includes multiple cubic polynomials S(x).

[0046] Combined with the above example, the obtained geometric feature data {(x i , y i ) | x ∈ R, y ∈ R}, the geometric feature data is divided into [-100, -50], [-50, 0], [0, 7.16], [7.16, 15.9], [15.9, 22.94], [22.94, 43.93], [43.93, 49.65], [49.65, 53.17], [53.17, 84.62], [84.62, 131.38], [131.38, 151.9], [8151.9, 200]. According to the divided multiple intervals, the above equations The following multiple cubic polynomials S(x) are obtained by spline interpolation:

[0047] It is easy to understand that the above multiple cubic polynomials S(x) are the terrain fitting functions. As Figure 2 shown in the original target cross-section contour line, Figure 3 is the fitted target cross-section contour line generated by the cubic polynomial S(x).

[0048] In this embodiment, by dividing the horizontal coordinate data into multiple intervals and calculating the terrain fitting function of each interval respectively, the terrain change of the target cross-section can be described more accurately, improving the accuracy and reliability of terrain fitting, and helping to calculate the debris flow related parameters more accurately.

[0049] In another alternative embodiment, a third-order polynomial model is selected, and then an optimization algorithm (such as the least squares method) is used to calculate the coefficients of the polynomial model. The calculated coefficients are substituted into the polynomial equation to obtain the terrain fitting function.

[0050] Step S103: The terminal device generates a cross-sectional area function and a wetted perimeter function through the terrain fitting function and the deepest mud level.

[0051] It should be understood that the deepest mud level is unknown, and the generated cross-sectional area function and wetted perimeter function are functions of h.

[0052] In an alternative embodiment, the cross-sectional area function is The wetted perimeter function is h is the deepest mud level, a(h) is the left intersection point of the terrain fitting function and the deepest mud level line, b(h) is the right intersection point of the terrain fitting function and the deepest mud level line. For specific reference, Figure 3 Example content.

[0053] In this embodiment, by calculating the cross-sectional area and wetted perimeter through integration, the complex contour of the irregular gully cross-section can be accurately adapted, ensuring the accuracy of the calculation results and avoiding the errors caused by simple approximation.

[0054] In another alternative implementation, the terrain fitting function can also be converted into a three-dimensional model, and the cross-sectional shape can be directly constructed using CAD or GIS software, enabling researchers to more intuitively calculate the area and wetted perimeter of the cross-section with an irregular shape.

[0055] Step S104: The terminal device substitutes the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level.

[0056] Exemplarily, the Manning formula is where Q is the peak debris flow discharge, I is the longitudinal slope of the cross-section, and n is the channel roughness. Substituting the above cross-sectional area function and wetted perimeter function into the Manning formula, a Manning formula with only the deepest mud level h unknown is obtained. Then, substituting the known peak debris flow discharge, longitudinal slope of the cross-section, and channel roughness into the Manning formula, the deepest mud level can be calculated.

[0057] For the method for calculating debris flow parameters provided by the embodiments of the present application, the terminal device obtains the horizontal coordinate data and elevation data of the target cross-section on the debris flow path, fits the terrain fitting function to ensure the accuracy and integrity of the terrain information, and then uses the relationship between the terrain fitting function and the cross-sectional area and wetted perimeter. Taking the deepest mud level as an unknown parameter, the cross-sectional area function and wetted perimeter function for the deepest mud level are derived, and these functions are incorporated into the Manning formula, so that a relatively accurate deepest mud level can be calculated, facilitating further research on debris flow by researchers.

[0058] In an alternative embodiment, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thereby obtaining the deepest mud level, the method further includes: substituting the deepest mud level into the cross-sectional area function and the wetted perimeter function to obtain the cross-sectional area and the wetted perimeter; and obtaining the hydraulic radius based on the cross-sectional area and the wetted perimeter.

[0059] Combined with the above example, substitute the deepest mud level h into the cross-sectional area function and the wetted perimeter function to obtain a cross-sectional area of 15 square meters, a wetted perimeter of 18 meters, and a hydraulic radius of A / C = 15 / 18 = 0.83 meters.

[0060] In this embodiment, more accurate cross-sectional area and wetted perimeter can be obtained based on the deepest mud level, thereby calculating a more reliable hydraulic radius, providing a scientific basis for evaluating the hydrodynamic behavior, risk prediction, and prevention and control measures design of debris flow.

[0061] In an alternative embodiment, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thereby obtaining the deepest mud level, the method further includes: substituting the deepest mud level into the cross-sectional area function to obtain the cross-sectional area of the target cross-section; and obtaining the debris flow velocity based on the cross-sectional area.

[0062] Combined with the above example, substitute the obtained cross-sectional area and wetted perimeter, as well as the known cross-sectional longitudinal slope drop and channel roughness, into the Manning-Strauss formula or the Darcy formula to solve for the debris flow velocity.

[0063] In this embodiment, calculating the debris flow velocity based on the cross-sectional area provides highly accurate relevant parameters for disaster assessment, greatly enhancing the timeliness and accuracy of debris flow monitoring and risk prevention and control.

[0064] In an alternative embodiment, after substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level and thereby obtaining the deepest mud level, the method further includes: comparing the deepest mud level, the hydraulic radius, and the debris flow velocity with a preset deepest mud level, a preset hydraulic radius, and a preset debris flow velocity respectively to obtain a deepest mud level difference, a hydraulic radius difference, and a velocity difference; and determining the risk level based on the deepest mud level difference, the hydraulic radius difference, and the velocity difference.

[0065] It is easy to understand that the preset deepest mud level, the preset hydraulic radius, and the preset debris flow velocity can be set arbitrarily according to the actual environment, and the present application does not make specific limitations thereto.

[0066] Exemplarily, the preset deepest mud level is 2 meters, the preset hydraulic radius is 3 meters, and the preset debris flow velocity is 10 m / s. Given that h is 1.5 meters, the hydraulic radius is 2.5 meters, and the debris flow velocity is 8 m / s, the differences in the deepest mud level, hydraulic radius, and velocity are 0.5 meters, 0.5 meters, and -2 m / s respectively. Optionally, the calculated differences can be compared with the preset differences to determine whether the differences are greater than the preset differences, thereby determining the risk level. Alternatively, the calculated differences can be displayed to the researchers to indicate to the researchers to determine the risk level.

[0067] In this embodiment, by obtaining the characteristic parameters related to the debris flow and calculating the parameter differences, it is possible to provide a scientific basis for debris flow disaster warning and risk control, enhance the pertinence and timeliness of preventive measures, and thus effectively improve the regional safety guarantee ability and emergency response efficiency.

[0068] It can be understood that in order for the terminal device to implement Figure 2 the functions described above, it includes the corresponding hardware and / or software modules for executing each function. Combining the steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving the hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to exceed the scope of the present application.

[0069] In this embodiment, the terminal device can be divided into function modules according to the above method examples. For example, each different function module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0070] In the case of dividing each function module corresponding to each function, Figure 4 shows a possible schematic diagram of the terminal device 400 involved in the above embodiment. The terminal device 400 includes: a first generation module 401, configured to obtain the horizontal coordinate data of the target section on the debris flow path and the elevation data corresponding to the horizontal coordinate data, and generate geometric feature data; a fitting module 402, configured to fit the terrain fitting function corresponding to the target section through the geometric feature data; a second generation module 403, configured to generate a cross-sectional area function and a wetted perimeter length function through the terrain fitting function and the deepest mud level; an obtaining module 404, configured to substitute the cross-sectional area function and the wetted perimeter length function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level.

[0071] In an alternative implementation of the embodiment of the present application, the fitting module 402 is further configured to construct a cubic polynomial S(x), where the cubic polynomial satisfies S(xi) = f(xi), S'(xi) = f'(xi), S''(xi) = f''(xi), where f(x) is the target cross-section terrain function and xi is the horizontal coordinate data; substitute the geometric feature data into the cubic polynomial S(x) to calculate the terrain fitting function.

[0072] In an alternative implementation of the embodiment of the present application, the fitting module 402 is further configured to divide the horizontal coordinate data into multiple intervals; substitute the partial geometric feature data corresponding to each interval in the multiple intervals into the cubic polynomial S(x), and calculate the terrain fitting function through spline interpolation. The terrain fitting function includes multiple cubic polynomials S(x).

[0073] In an alternative implementation of the embodiment of the present application, the fitting module 402 is further configured that the cross-sectional area function is The wetted perimeter length function is where h is the deepest mud level, a(h) is the left intersection point of the terrain fitting function and the deepest mud level line, and b(h) is the right intersection point of the terrain fitting function and the deepest mud level line.

[0074] In an alternative implementation of the embodiment of the present application, the fitting module 402 is further configured to substitute the deepest mud level into the cross-sectional area function and the wetted perimeter length function to obtain the cross-sectional area and the wetted perimeter length; obtain the hydraulic radius according to the cross-sectional area and the wetted perimeter length.

[0075] In an alternative implementation of the embodiment of the present application, the obtaining module 404 is further configured to substitute the deepest mud level into the cross-sectional area function to obtain the cross-sectional area of the target cross-section; obtain the debris flow velocity according to the cross-sectional area.

[0076] In an alternative implementation of the embodiment of the present application, the obtaining module 404 is further configured to compare the deepest mud level, the hydraulic radius, and the debris flow velocity with the preset deepest mud level, the preset hydraulic radius, and the preset debris flow velocity respectively to obtain the deepest mud level difference, the hydraulic radius difference, and the velocity difference; determine the risk level according to the deepest mud level difference, the hydraulic radius difference, and the velocity difference.

[0077] The present application also discloses an electronic device. Referring to Figure 5 , Figure 5 is a schematic structural diagram of an electronic device disclosed in the embodiment of the present application. The electronic device 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 505, and at least one communication bus 502.

[0078] Among them, the communication bus 502 is used to realize the connection and communication between these components.

[0079] Among them, the user interface 503 may include a display screen and a camera. Optionally, the user interface 503 may further include a standard wired interface and a wireless interface.

[0080] Among them, the network interface 504 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0081] Among them, the processor 501 may include one or more processing cores. The processor 501 connects various parts within the entire server through various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and by calling the data stored in the memory 505, the processor 501 performs various functions of the server and processes data. Optionally, the processor 501 may be implemented in at least one of the hardware forms of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 501 may integrate one or a combination of several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above modem may not be integrated into the processor 501 and may be implemented separately through a single chip.

[0082] Among them, the memory 505 may include a Random Access Memory (RAM), or may also include a Read-Only Memory. Optionally, the memory 505 includes a non-transitory computer-readable storage medium. The memory 505 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 505 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store the data involved in the above-mentioned method embodiments. Optionally, the memory 505 may also be at least one storage device located far from the aforementioned processor 501. Refer to Figure 5 , the memory 505 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a method of calculating debris flow parameters.

[0083] In Figure 5 In the electronic device 500 shown, the user interface 503 is mainly used to provide an input interface for the user to obtain the data input by the user; and the processor 501 can be used to call the application program for a method of calculating debris flow parameters stored in the memory 505. When executed by one or more processors 501, the electronic device 500 is caused to execute one or more of the methods as described in the above embodiments. It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0084] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0085] In several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be through some service interfaces. The indirect couplings or communication connections of devices or units can be in electrical or other forms.

[0086] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, in each embodiment of this application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0088] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of this application. And the aforementioned memory includes: various media such as USB flash drives, mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0089] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure still fall within the scope covered by the present disclosure. Those skilled in the art will easily think of other implementation schemes of the present disclosure after considering the specification and the disclosure of the practical truth.

[0090] This application is intended to cover any variations, uses, or adaptations of the present disclosure, which follow the general principles of the present disclosure and include well-known knowledge or conventional technical means in the technical field not described in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for calculating debris flow parameters, characterized in that: include: Acquire horizontal coordinate data of a target section on a debris flow path and elevation data corresponding to the horizontal coordinate data to generate geometric feature data; Fitting a terrain fitting function corresponding to the target section through the geometric feature data; Generate a cross-sectional area function and a wet perimeter length function through the terrain fitting function and the deepest mud position; Substituting the cross-sectional area function and the wetted perimeter length function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level; The cross-sectional area function is The wet perimeter function is h is the deepest mud level, a(h) is the horizontal coordinate of the left intersection of the terrain fitting function and the deepest mud level line, and b(h) is the horizontal coordinate of the right intersection of the terrain fitting function and the deepest mud level line.

2. The method according to claim 1, characterized in that The step of fitting the terrain fitting function corresponding to the target section through the geometric feature data includes: Construct a cubic polynomial S(x), the cubic polynomial satisfies S(xi)=f(xi), S'(xi)=f'(xi), S"(xi)=f"(xi), wherein f(x) is the target section terrain function, and xi is the horizontal coordinate data; The geometric feature data is substituted into the cubic polynomial S(x) to calculate the terrain fitting function.

3. The method according to claim 2, characterized in that Before calculating the terrain fitting function from the geometric feature data, the method further includes: Dividing the horizontal coordinate data into a plurality of intervals; Substitute part of the geometric feature data corresponding to each of the multiple intervals into the cubic polynomial S(x), and calculate the terrain fitting function through spline interpolation method. The terrain fitting function includes multiple cubic polynomials S(x).

4. The method according to claim 3, characterized in that After substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level, the method further includes: Substituting the deepest mud level into the cross-sectional area function and the wetted perimeter function to obtain the cross-sectional area and the wetted perimeter; The hydraulic radius is obtained according to the cross-sectional area and the wetted perimeter.

5. The method according to claim 4, characterized in that After substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level, the method further includes: Substituting the deepest mud level into the cross-sectional area function to obtain the cross-sectional area of ​​the target cross-section; The debris flow velocity is obtained according to the cross-sectional area.

6. The method according to claim 5, characterized in that After substituting the cross-sectional area function and the wetted perimeter function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level, the method further includes: The deepest mud level, the hydraulic radius and the debris flow velocity are compared with the preset deepest mud level, the preset hydraulic radius and the preset debris flow velocity respectively to obtain the deepest mud level difference, the hydraulic radius difference and the velocity difference; The risk level is determined according to the deepest mud level difference, the hydraulic radius difference and the flow velocity difference.

7. A terminal device, characterized in that: The terminal device comprises: A first generating module is used to obtain horizontal coordinate data of a target section on a debris flow path and elevation data corresponding to the horizontal coordinate data, and generate geometric feature data; A fitting module, used for fitting a terrain fitting function corresponding to the target section through the geometric feature data; A second generating module is used to generate a cross-sectional area function and a wet perimeter length function through the terrain fitting function and the deepest mud level; an obtaining module is used to substitute the cross-sectional area function and the wet perimeter length function into the Manning formula to obtain the Manning formula for the deepest mud level, thereby obtaining the deepest mud level; The cross-sectional area function is The wet perimeter function is h is the deepest mud level, a(h) is the horizontal coordinate of the left intersection of the terrain fitting function and the deepest mud level line, and b(h) is the horizontal coordinate of the right intersection of the terrain fitting function and the deepest mud level line.

8. An electronic device, characterized in that: The electronic device (500) comprises a processor (501), a memory (505), a user interface (503) and a network interface (504), wherein the memory (505) is used to store instructions, the user interface (503) and the network interface (504) are used to communicate with other devices, and the processor (501) is used to execute the instructions stored in the memory (505) so that the electronic device (500) executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is performed.

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