Method for calculating storage capacity of debris flow dam and iterative optimization of dam height based on point cloud and tin model

Abstract

This invention discloses a method for calculating the reservoir capacity and iteratively optimizing the dam height of debris flow dams based on point cloud and TIN models, belonging to the field of debris flow disaster prevention and control engineering technology. First, original ground point cloud data of the dam site area is acquired and preprocessed. TIN models of the original gully and the post-dam siltation surface are constructed separately. The design reservoir capacity is calculated using the triangular prism volume integral method, and the siltation line can be automatically generated and the siltation visualization results are output. Simultaneously, with accurate reservoir capacity as the core indicator, a verification mechanism between the reservoir capacity and the required reservoir capacity is established. The dam height is iteratively optimized by adjusting the elevation of the dam crest centerline until the reservoir capacity meets the requirements. This invention achieves rapid and high-precision calculation of the design reservoir capacity, eliminating reliance on manual operation. It also constructs a standardized reservoir capacity-dam height iterative process, achieving precise matching between dam height and reservoir capacity, balancing engineering disaster control effectiveness and economy. The results are compatible with general engineering formats and applicable to complex gully terrain, providing reliable technical support for the precise design of dams.

Description

Technical Field

[0001] This invention relates to the field of debris flow disaster prevention and control engineering technology, and more specifically to a method for calculating the reservoir capacity and iteratively optimizing the dam height of debris flow retaining dams based on point cloud and TIN models. Background Technology

[0002] Debris flows are a type of geological hazard characterized by complex causes, sudden onset, high velocity, high solids content, and high destructiveness, widely distributed in the mountainous areas of southwestern my country. As a primary retaining structure in debris flow prevention and control projects, the rationality of the design of sediment-trapping dams directly affects the disaster control effectiveness and economic efficiency. The reservoir capacity design of sediment-trapping dams is a core aspect of the engineering design process, directly determining their ability to retain solid debris and their service life.

[0003] Currently, in domestic engineering practice, the three methods for calculating the reservoir capacity of sediment-trapping dams specified in Appendix G of the "Design Code for Debris Flow Prevention Engineering" (T / CAGHP021-2018) are commonly used: contour line method, cross-section method, and empirical formula method. All of these methods require manual plotting of backfill lines, resulting in low automation, high workload, and difficulty in fully utilizing high-precision point cloud topographic data obtained from lidar and UAV photogrammetry. This leads to low terrain reconstruction accuracy and significant deviations in reservoir capacity calculation results, failing to provide accurate data support for subsequent dam height design.

[0004] Meanwhile, existing technologies have significant shortcomings in the joint application of reservoir capacity calculation and dam height design, and have not yet formed a complete technical system of "accurate reservoir capacity calculation → dam height assumption → reservoir capacity verification → dam height iteration," specifically reflected in: 1. For example, the invention patent with authorization announcement number CN111639385B and title "A method for calculating the design height of a debris flow check dam" uses the horizontal length of backfilling after the check dam as the core verification indicator. It does not take the reservoir capacity meeting the standard as the direct goal of the dam height design, but only uses the backfilling parameters to infer the dam height. This is likely to lead to a mismatch between the actual reservoir capacity corresponding to the designed dam height and the required retention capacity of the project. Either the reservoir capacity is insufficient, which will cause the risk of debris flow overturning the dam, or the dam height is too high, which will cause waste of project costs. 2. For example, the invention patent with authorization announcement number CN113282997B and title "Method and application for calculating the longitudinal gradient of siltation in debris flow dam reservoir" only focuses on the accurate calculation of the single parameter of longitudinal gradient of siltation in the reservoir, without linking it with reservoir capacity calculation and dam height design. The calculation result of the longitudinal gradient of siltation cannot directly serve the reservoir capacity calculation, nor does it form a dam height adjustment logic based on siltation parameters. The technical means are isolated and cannot support the accurate design of dam height. 3. For example, the invention patent application with publication number CN117494286A, entitled "A design method, device and equipment for a sediment trap dam", optimizes the dam height through numerical simulation. Although it considers the influence of dam structure parameters on debris flow prevention, it does not combine the high-precision reservoir capacity calculation results to verify the dam height. It only determines the design height through simulation parameter assumptions and lacks actual verification of the core indicator of reservoir capacity. The rationality and accuracy of the dam height design are limited.

[0005] Furthermore, even though some existing technologies attempt to combine reservoir capacity with dam height, the low accuracy of basic reservoir capacity calculations and the lack of standardized iterative verification processes mean that dam height design still relies heavily on engineers' experience and judgment, making it impossible to achieve automated iterative optimization of dam height based on quantified reservoir capacity data. Therefore, there is an urgent need to develop a high-precision method for calculating the reservoir capacity of debris flow dams, fully utilizing modern surveying point cloud data to improve the automation and accuracy of reservoir capacity calculations. Simultaneously, based on this accurate reservoir capacity calculation result, an iterative verification process for reservoir capacity and dam height should be established to further optimize the application of the reservoir capacity calculation method, addressing the core pain point of mismatch between dam height design and reservoir capacity requirements in existing technologies, and providing technical support for the precise design of debris flow dams. Summary of the Invention

[0006] To overcome the defects and shortcomings of the existing technologies, this invention provides a method for calculating the reservoir capacity and iteratively optimizing the dam height of debris flow dams based on point cloud and TIN models. The purpose of this invention is twofold: first, to fully utilize point cloud data from modern surveying to improve the automation and accuracy of reservoir capacity calculation and increase computational efficiency; second, to establish an iterative verification process for reservoir capacity-dam height based on the accurate reservoir capacity calculation results, thereby enabling the further efficient application of the reservoir capacity calculation method, solving the core pain point of mismatch between dam height design and reservoir capacity requirements in the existing technologies, and providing technical support for the accurate design of debris flow dams.

[0007] To address the problems existing in the prior art, the present invention is achieved through the following technical solution.

[0008] The first aspect of this invention provides a method for calculating the reservoir capacity of debris flow dams based on point cloud and TIN models, the method comprising the following steps: S1. For the selected dam site area, obtain the original ground point cloud data of the reservoir area and the surrounding set range before the construction of the dam. S2. The raw ground point cloud data obtained in step S1 is preprocessed, including point cloud data coordinate calculation, outlier removal and classification; then the preprocessed point cloud data is sparsified using the model key point extraction method. S3. Based on the point cloud data after sparsification in step S2, construct the original irregular triangular mesh terrain model of the gully ground. S4. Based on the design dam crest centerline, determine the design dam height and obtain the three-dimensional spatial coordinates (X1,Y1,Z0) and (X2,Y2,Z0) of any two points on the dam crest centerline; determine the design dam backfilling longitudinal gradient i. Treating the siltation surface of the silt-trapping dam as an approximate inclined plane, the spatial coordinates of any point on the siltation surface are determined based on the design of the dam crest centerline and the siltation longitudinal gradient i: (1); In the formula, Z0 is the elevation of the siltation surface of the silt-retaining dam corresponding to the plane coordinates (X,Y), in meters; Z0 is the design crest elevation of the silt-retaining dam, in meters; i is the design longitudinal gradient of the siltation backfilling dam, dimensionless. Using the original point cloud planar coordinates (X,Y) in the point cloud data after the S2 step sparsification process, the three-dimensional coordinates (X,Y,Z) of the sedimentation surface of the silt-trapping dam are generated according to the above formula (1). hy The data is used to generate point cloud data of the backfill surface after the construction of the silt-trapping dam; the scope of the point cloud data of the backfill surface after the construction of the silt-trapping dam includes the dam site area and the upstream reservoir area; based on the point cloud data of the backfill surface after the construction of the silt-trapping dam, a virtual irregular triangular mesh terrain model of the dam is constructed. S5. Based on the difference between the original irregular triangular network terrain model of the gully surface and the virtual irregular triangular network terrain model after the construction of the dam, calculate the design reservoir capacity of the dam; the calculation process is as follows: S51. The boundary for volume calculation is defined as the central axis of the dam crest and the upstream reservoir area, which is divided into the calculation area. S52. Using the plane triangular face of the irregular triangular network terrain model as the basic unit, the calculation field is divided into several irregular triangular prisms. The volume of each irregular triangular prism is calculated, and the design capacity of the silt-trapping dam is calculated based on the integral method.

[0009] More preferably, in step S52, the volume calculation formula for the irregular triangular prism is: (2); In the formula, Let m be the volume of the j-th irregular triangular prism. 3 ; Let m be the projected area of ​​the top and bottom triangular faces of the j-th irregular triangular prism. 2 ; Let each represent the elevation of the siltation surface of the trapping dam at the three vertices of the upper triangle of the j-th irregular triangular prism, in meters; Let represent the original elevations of the three vertices of the lower triangle of the j-th irregular triangular prism, in meters (m). The formula for calculating the design reservoir capacity of the silt trap dam based on the integral method is as follows: (3); where, This indicates the design capacity of the silt trap dam, in meters (m). 3 ; Let m be the volume of the j-th irregular triangular prism. 3 ; n represents the number of irregular triangular prisms; when Only positive values ​​are included in the calculation.

[0010] Further preferred, in step S5, the original elevation Z corresponding to each original point cloud and the siltation surface elevation Z of the retaining dam are used. hy The elevation difference is used to obtain the boundary line where the siltation surface intersects the original topographic surface by using the elevation difference grid hierarchical extraction method. This boundary line is the siltation line of the silt-trapping dam reservoir area.

[0011] In a further preferred embodiment, in step S5, based on the elevation difference in the virtual irregular triangular network terrain model after the construction of the dam, spatial visualization results are generated. The spatial visualization results include contour maps of sedimentation thickness behind the dam and color maps of sedimentation thickness, so as to intuitively display the thickness and spatial distribution characteristics of debris flow accumulation.

[0012] In a further preferred embodiment, in step S5, the calculation results of the design reservoir capacity of the silt-trapping dam and the spatial visualization results are exported in a general engineering format. The general engineering format includes volume data tables in Excel format, backfill line maps in CAD format, and / or raster or vector data in Shapefile format, for use in engineering design or GIS platform integration.

[0013] In a further preferred embodiment, in step S4, the longitudinal gradient i of the designed sediment trap dam is determined according to the method in T / CAGHP021-2018 "Design Code for Debris Flow Prevention Engineering". The calculation formula is as follows: (3); In the formula, i represents the longitudinal gradient of the designed silt-trapping dam. The original slope of the ditch. The internal friction angle of the debris flow.

[0014] More preferably, in step S1, the original ground point cloud data is obtained using an airborne lidar scanning system, an unmanned aerial vehicle oblique photography system, or a ground 3D laser scan, and the sampling density of the original ground point cloud data is 15-20 points / m. 2 The collection area covers the entire area of ​​the proposed dam site and the upstream reservoir, extending outwards by 50-100m.

[0015] In a further preferred embodiment, during the preprocessing of the original ground point cloud data in step S2, the point cloud data coordinates are calculated to convert the data into a unified planar geographic coordinate system and elevation system; a filtering algorithm is used to identify noise points, duplicate points, reflection anomalies, and / or anomalies caused by instrument errors during the scanning process, and non-ground points formed by vegetation, buildings, and / or suspended objects are removed; for areas with missing point cloud data, the triangular mesh linear interpolation method, the Kriging interpolation method, or the inverse distance weighting method is used to fill the holes.

[0016] Furthermore, for LiDAR point cloud data, a rule-based classification algorithm or a machine learning-based classification method is used to remove non-ground points and retain only the point cloud data of ground points.

[0017] In a further preferred embodiment, in step S3, the Delaunay triangulation algorithm or the point-by-point insertion method is used to construct the original irregular triangular network terrain model of the gully surface; in step S4, the Delaunay triangulation algorithm or the point-by-point insertion method is used to construct the virtual irregular triangular network terrain model after the construction of the dam. The construction methods used in steps S3 and S4 are the same.

[0018] The second aspect of this invention provides an iterative optimization method for the height of debris flow dams based on point cloud and TIN models, including steps S1-S5 of the debris flow dam capacity calculation method based on point cloud and TIN models described in the first aspect, and further including: S6. Calculate the design reservoir capacity of the silt trap dam obtained in step S5. With demand and storage capacity If a comparison is made, If the height of the dam is too high, then the design height of the dam should be lowered, and steps S4-S5 should be iterated. If the design height of the silt-trapping dam is too low, then the design height of the silt-trapping dam should be increased, and steps S4-S5 should be iterated until... In the formula, To meet the demand for storage capacity Storage capacity redundancy .

[0019] Compared with the prior art, the beneficial technical effects of the present invention are as follows: This invention achieves rapid and accurate calculation of the design capacity of debris flow retaining dams by fusing point cloud data with TIN models. Based on the calculation results, a standardized iterative optimization process for capacity-dam height is constructed. Compared with existing technologies, this invention achieves multiple breakthroughs in terms of calculation accuracy, efficiency, automation, and the rationality and economy of dam height design. The specific technical effects are as follows: 1. This invention utilizes high-precision point cloud data to achieve accurate calculation of reservoir capacity, providing reliable data support for silt-trapping dam design. Based on raw ground point cloud data acquired using modern surveying technologies such as airborne lidar and UAV oblique photography, this invention preserves the high-precision spatial characteristics of the original gully topography through standardized preprocessing procedures including coordinate calculation, outlier removal, cavity filling, and sparsification. The point cloud sampling density reaches 15-20 points / m², significantly improving the accuracy of topographic reconstruction from the data source compared to the low-precision topographic maps relied upon by traditional contour line and cross-section methods. Furthermore, this invention employs the Delaunay triangulation algorithm to construct the original gully ground TIN model and the post-dam siltation surface TIN model. By accurately fitting complex gully topography with triangular faces, it avoids the spatial information loss caused by the simplification of two-dimensional graphics in traditional methods, and can realistically reconstruct the complex geomorphic features of the gully, such as steep slopes and narrow valley sections. Based on this, using the planar triangular facets of the TIN model as the basic unit, the calculation field is divided into several irregular triangular prisms. The design reservoir capacity is calculated by the triangular prism volume integral method, which achieves a precise match between the design reservoir capacity and the actual terrain. The calculation results are closer to the actual accumulation volume of debris flow solid materials, which greatly reduces the reservoir capacity calculation deviation and provides core quantitative data support for the subsequent accurate design of the dam height. This solves the technical problem that the traditional reservoir capacity calculation results are low in accuracy and cannot provide an effective reference for dam height design.

[0020] 2. This invention enables rapid, programmed calculation of reservoir capacity based on design parameters, significantly improving design efficiency and reducing labor costs. Based on core design parameters such as the dam crest centerline, design dam height, and longitudinal gradient of the backfilling, the invention accurately derives the three-dimensional coordinates of any point on the backfilling surface using formulas. It directly uses the planar coordinates (X, Y) of the pre-processed original point cloud to generate point cloud data for the backfilling surface, eliminating the need for manual plotting of backfilling lines and completely eliminating the cumbersome process of manual measurement, point-by-point calculation, and list accumulation in traditional methods. Meanwhile, the reservoir capacity calculation process relies on the triangulation and triangular prism integration of the TIN model to achieve procedural processing. From point cloud data preprocessing and dual TIN model construction to reservoir capacity calculation, no manual intervention is required throughout the entire process. It can quickly complete the entire calculation process from design parameter input to design reservoir capacity output. Compared with the manual operation mode of traditional contour line method and cross section method, it significantly shortens the time consumption of reservoir capacity calculation, improves the work efficiency in the early stage of sediment trap design, and avoids subjective errors caused by manual operation. It realizes rapid and standardized calculation of design reservoir capacity, and meets the rapid and accurate design requirements of modern debris flow prevention and control projects.

[0021] 3. Constructing a dual TIN model comparison system to integrate reservoir capacity calculation and siltation characteristic analysis, enriching design reference dimensions. This invention constructs a TIN model of the original gully surface before dam construction and a TIN model of the silted surface after dam construction. Utilizing the elevation difference between the two models, it can not only calculate the designed reservoir capacity through volume integration, but also automatically generate the siltation line of the dam reservoir area based on the difference between the original point cloud elevation and the silted surface elevation. Simultaneously, it outputs spatial visualization results such as contour maps and siltation thickness color maps after the dam. This design integrates reservoir capacity calculation and spatial analysis of siltation characteristics. While obtaining accurate reservoir capacity values, it can also intuitively display the accumulation thickness and spatial distribution characteristics of debris flow solid materials in the reservoir area after the dam, clearly defining the siltation range. This provides designers with multi-dimensional intuitive references for judging the rationality of reservoir capacity and optimizing the dam's location and size, overcoming the limitations of traditional reservoir capacity calculation methods that can only output a single value and cannot reflect the spatial characteristics of siltation, making silt-trapping dam design more targeted and scientific.

[0022] 4. A standardized iterative optimization process for dam height is constructed based on accurate reservoir capacity data to achieve precise matching between dam height and reservoir capacity, balancing disaster control effectiveness and engineering economy. This invention uses the high-precision design reservoir capacity calculation results as the core verification indicator for dam height design, and constructs a standardized reservoir capacity-dam height iterative optimization process of "reservoir capacity calculation → reservoir capacity verification → dam height adjustment → iterative calculation". By comparing the calculated design reservoir capacity with the required reservoir capacity for the project, and combining the reservoir capacity redundancy threshold, the invention accurately judges whether the design dam height is too high or too low, and achieves iterative optimization of the dam height by adjusting the elevation of the dam crest centerline until the design reservoir capacity meets the requirements of "required reservoir capacity + reasonable redundancy". This iterative process completely changes the existing design mode that uses siltation length as a verification indicator or relies on empirical assumptions about dam height. It directly binds dam height design to the core requirement of debris flow solid material interception, effectively avoiding the risk of debris flow overturning caused by insufficient reservoir capacity due to excessively low dam height. At the same time, it also prevents the waste of engineering materials and construction costs caused by excessively high dam height. It achieves a precise match between the dam height and reservoir capacity, so that the dam height design not only meets the engineering requirements of debris flow prevention and control, but also has optimal economic efficiency, solving the core pain point of mismatch between dam height design and reservoir capacity requirements in existing technologies.

[0023] 5. The technology boasts strong compatibility and wide applicability, adaptable to different gully terrains and surveying data types, demonstrating excellent engineering practicality. The point cloud data acquisition method of this invention is compatible with various methods such as airborne LiDAR, UAV oblique photography, ground 3D laser scanning, and even total station manual measurement. It can be flexibly selected based on actual conditions at the engineering site, such as no-fly zones and vegetation coverage. The point cloud preprocessing workflow is also adaptable to different types of point cloud data, including LiDAR point clouds and image reconstruction point clouds. Simultaneously, the TIN model's triangulation algorithm can flexibly adapt to the complex terrain features of debris flow gullies in the southwestern mountainous region, unaffected by gully width-to-depth ratios or terrain undulations. Compared to the limitations of traditional methods applicable only to regular gullies, this invention can be widely applied in the design of sediment-trapping dams for various debris flow gullies. Furthermore, the calculation results and visualization outputs of this invention can be exported to common engineering formats such as Excel, CAD, and Shapefile, enabling direct integration with existing engineering design software and GIS platforms without additional format conversion. This significantly improves the engineering practicality and operability of the technical solution, facilitating rapid implementation in debris flow prevention engineering design.

[0024] 6. This invention achieves a significant expansion of reservoir capacity calculation methods, upgrading from "single reservoir capacity calculation" to "coordinated reservoir capacity-dam height design." The reservoir capacity calculation method of this invention is not an independent technical step, but rather serves as the core foundation for iterative optimization of dam height in debris flow control dams. Through precise and rapid reservoir capacity calculation, it transforms dam height design from "experience-driven" to "data-driven," enabling further efficient application of reservoir capacity calculation methods. Compared to existing technologies where reservoir capacity calculation and dam height design are disconnected and parameter calculations are isolated, this invention organically integrates point cloud-TIN model reservoir capacity calculation, siltation characteristic analysis, and iterative dam height optimization into a complete technical system. This upgrade from "single reservoir capacity calculation" to "coordinated reservoir capacity-dam height design" provides a complete technical solution for the precise and scientific design of debris flow control dams, filling the gap in existing technologies that lack an integrated technical system of "precise reservoir capacity calculation - iterative dam height optimization," and promoting the development of debris flow prevention engineering design towards digitalization and precision. Attached Figure Description

[0025] To more clearly illustrate the technical solution of the present invention, the implementation process and embodiments of the present invention will be further described below with reference to the accompanying drawings. The drawings are only used to assist in understanding the technical solution of the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0026] Figure 1 This is a flowchart of the method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN model according to the present invention. Figure 2 This is a flowchart of the iterative optimization method for debris flow retaining dam height based on point cloud and TIN model of the present invention. Figure 3 This is a diagram showing the calculated reservoir capacity of the silt-trapping dam according to an embodiment of the present invention; Figure 4 The images show contour lines and color maps of siltation thickness within the silt-trapping dam reservoir, as described in this embodiment of the invention. Detailed Implementation

[0027] To more clearly illustrate the technical solution of the present invention, the implementation process and embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0028] Example 1 As a preferred embodiment of the present invention, please refer to the appendix to the specification. Figure 1 As shown in the figure, this embodiment discloses a method for calculating the reservoir capacity of debris flow dams based on point cloud and TIN models. The method includes the following steps: S1. For the selected dam site area, obtain the original ground point cloud data of the reservoir area and the surrounding set range before the construction of the dam.

[0029] S2. The raw ground point cloud data obtained in step S1 is preprocessed, and then the preprocessed point cloud data is sparsified using the model key point extraction method. The preprocessing includes point cloud data coordinate calculation, outlier removal and classification.

[0030] S3. Based on the point cloud data after sparse processing in step S2, construct the original irregular triangular mesh terrain model of the gully ground; use the Delaunay triangulation algorithm to construct the original irregular triangular mesh terrain model of the gully ground; as another example of this step, use the point-by-point insertion method to construct the original irregular triangular mesh terrain model of the gully ground.

[0031] S4. Construct a virtual irregular triangular network terrain model after the construction of the silt-retaining dam; specifically including the following steps: S41. Based on the design centerline of the dam crest, determine the design dam height and obtain the three-dimensional spatial coordinates (X1,Y1,Z0) and (X2,Y2,Z0) of any two points on the centerline of the dam crest.

[0032] S42. Determine the longitudinal gradient i of the designed sediment trap dam; As an example for this step, the longitudinal gradient i of the designed sediment trap dam is determined according to the method in T / CAGHP021-2018 "Code for Design of Debris Flow Prevention Engineering". The calculation formula is as follows: (3); where i represents the longitudinal gradient of the designed silt-trapping dam. The original slope of the ditch. This represents the internal friction angle of the debris flow. As another example of this step, other existing methods can also be used to determine the longitudinal gradient of the design silt-trapping dam.

[0033] S43. Considering the siltation surface of the silt-trapping dam as an approximate inclined plane, determine the spatial coordinates of any point on the siltation surface of the silt-trapping dam based on the designed dam crest centerline and the siltation longitudinal gradient i: (1); In the formula, Z0 represents the elevation of the siltation surface of the silt-retaining dam corresponding to the plane coordinates (X,Y), in meters; Z0 represents the design crest elevation of the silt-retaining dam, in meters; and i represents the design longitudinal gradient of the siltation backfilling of the silt-retaining dam, dimensionless.

[0034] S44. Using the original point cloud plane coordinates (X,Y) in the point cloud data after sparsification in step S2, generate the three-dimensional coordinates (X,Y,Z) of the sedimentation surface of the silt-trapping dam according to the above formula (1). hy This generates point cloud data of the siltation surface after the construction of the silt-trapping dam. S45. The point cloud data of the siltation surface after the construction of the silt-trapping dam includes the dam site area and the upstream reservoir area. Based on the point cloud data of the siltation surface after the construction of the silt-trapping dam, a virtual irregular triangular mesh terrain model of the dam is constructed. As an example of this step, the Delaunay triangulation algorithm is used to construct the virtual irregular triangular mesh terrain model of the dam. As another example of this step, the point-by-point insertion method is used to construct the virtual irregular triangular mesh terrain model of the dam. The construction method used in this step is consistent with the construction method in step S3 to overcome model errors caused by the construction method.

[0035] S5. Based on the difference between the original irregular triangular network topographic model of the gully before dam construction and the virtual irregular triangular network topographic model after dam construction, calculate the reservoir capacity of the silt-trapping dam, as shown in the appendix to the instruction manual. Figure 3 As shown, the details are as follows: S51. The boundary for volume calculation is defined as the central axis of the dam crest and the upstream reservoir area, which is divided into the calculation area. S52. Using the plane triangular face of the irregular triangular network terrain model as the basic unit, the calculation field is divided into several irregular triangular prisms. The volume of each irregular triangular prism is calculated, and the design capacity of the silt-trapping dam is calculated based on the integral method.

[0036] Specifically, the formula for calculating the volume of the irregular triangular prism is as follows: (2); In the formula, Let m be the volume of the j-th irregular triangular prism. 3 ; Let m be the projected area of ​​the top and bottom triangular faces of the j-th irregular triangular prism. 2 ; Let each represent the elevation of the siltation surface of the trapping dam at the three vertices of the upper triangle of the j-th irregular triangular prism, in meters; Let represent the original elevations of the three vertices of the lower triangle of the j-th irregular triangular prism, in meters (m). The formula for calculating the design reservoir capacity of the silt trap dam based on the integral method is as follows: (3); where, This indicates the design capacity of the silt trap dam, in meters (m). 3 ; Let m be the volume of the j-th irregular triangular prism. 3 ; n represents the number of irregular triangular prisms; when Only positive values ​​are included in the calculation.

[0037] Example 2 As another preferred embodiment of the present invention, this embodiment is a further detailed supplement and explanation of the technical solution of the present invention based on the above embodiment 1. As one implementation method of this embodiment, as shown in the appendix to the specification... Figure 3 As shown, step S5 further includes: S53, Based on the original elevation Z corresponding to each original point cloud and the siltation surface elevation Z of the retaining dam. hy The elevation difference is used to obtain the boundary line where the siltation surface intersects the original topographic surface by using the elevation difference grid hierarchical extraction method. This boundary line is the siltation line of the silt-trapping dam reservoir area.

[0038] As another embodiment of this invention, please refer to the appendix to the specification. Figure 4 As shown, step S5 further includes: S54. Based on the elevation difference in the virtual irregular triangular network terrain model after the construction of the dam, generate spatial visualization results. The spatial visualization results include contour maps of sedimentation thickness behind the dam and color maps of sedimentation thickness, so as to intuitively show the thickness and spatial distribution characteristics of debris flow accumulation.

[0039] It should be noted that there is no specific order between steps S53 and S54. They can be implemented individually, simultaneously, or sequentially as needed.

[0040] As another implementation of this embodiment, based on the above implementation, step S5 further includes: S55. Export the design reservoir capacity calculation results and spatial visualization results of the silt-trapping dam in a general engineering format, including volume data tables in Excel format, backfill line drawings in CAD format, and / or raster or vector data in Shapefile format, for use in engineering design or GIS platform integration.

[0041] Example 3 As another preferred embodiment of the present invention, this embodiment is a further detailed supplement and explanation of the technical solution of the present invention based on the above embodiment 1 or embodiment 2.

[0042] In one implementation of this embodiment, in step S1, the original ground point cloud data is obtained using an airborne lidar scanning system, an unmanned aerial vehicle oblique photography system, or a ground 3D laser scan, and the sampling density of the original ground point cloud data is 15-20 points / m. 2 The collection area covers the entire area of ​​the proposed dam site and the upstream reservoir, extending outwards by 50-100m.

[0043] As an example, when encountering no-fly zones or extremely dense vegetation, a handheld lidar can be used to acquire raw ground point cloud data. When instruments are limited, a total station or RTK can be used to manually select points and measure them one by one to obtain the three-dimensional coordinates (X, Y, Z) of each point, forming a sparse point cloud. The manual sampling density can be 25 points / m². 2 The measurements should be intensified at locations where the terrain changes abruptly.

[0044] As another implementation method of this embodiment, in step S2, when preprocessing the original ground point cloud data, the coordinates of the point cloud data should be calculated first to convert the data into a unified planar geographic coordinate system (such as CGCS2000) and elevation system. For point cloud data from multiple flights or multiple measurements, spatial registration is required to unify it into a continuous dataset. Then, algorithms such as statistical outlier removal and radius outlier removal are applied to remove noise, duplicate points, reflection anomalies, and anomalies caused by instrument errors during the scanning process, as well as non-ground points such as vegetation, buildings, and suspended objects. For LiDAR point cloud data, rule-based classification algorithms such as volume difference method and slope method or machine learning-based classification methods can be used to remove vegetation, buildings, and suspended objects, retaining only the "ground point" point cloud data. Sparse point clouds measured manually using a total station do not require processing. After point cloud denoising, filtering, and non-ground point removal, holes in areas with missing points are filled using triangular mesh linear interpolation, Kriging interpolation, or inverse distance weighting. Finally, for spatial point cloud data containing a large amount of high density, while ensuring accurate representation of terrain information, the point cloud data is sparsified by extracting model key points. The resulting point cloud density should be between points / 4 and 25 m² (larger values ​​can be used for larger databases).

[0045] Example 4 The preferred embodiments of the present invention are described in detail below with reference to specific engineering cases. In 2022, a debris flow gully in a certain county of a certain province erupted and destroyed 10 houses, causing direct economic losses of 2 million yuan. The present invention was practically applied in the design of the debris flow dam reservoir. The drainage area of ​​the debris flow gully is 4.78 km². 2 At an altitude of 1190–2465 m and a relative elevation difference of 1275 m, the exploration yielded a solid material ejection volume of 3.79 × 10⁻⁶ m for a debris flow with a frequency of P = 5% (once in 20 years). 4 m 3 Due to the limited drainage capacity at the mouth of the debris flow gully, a sediment trap needs to be designed within the gully to block solid material ejected by debris flows at a frequency of 1-2 times P=5%, which will be used as the design value for the sediment trap reservoir capacity.

[0046] The reservoir capacity of a silt-trapping dam is an important indicator for evaluating the ability to retain solid materials from debris flows. The calculation steps for the design reservoir capacity of a silt-trapping dam are as follows: S1. For the selected dam site area, obtain the original ground point cloud data of the reservoir area and a certain range around it before the construction of the dam: A drone equipped with an oblique photogrammetry system was used to acquire high-resolution image data within the dam site and upstream gully area. Post-processing generated 3D point cloud data with a point density of approximately 5 points / m², covering an area of ​​approximately 0.08 km². The oblique photogrammetry plane covered the entire area of ​​the proposed dam site and the upstream reservoir, extending approximately 100m downstream from the dam site and approximately 100m upstream from the estimated reservoir area.

[0047] S2. Raw point cloud data preprocessing, point cloud classification and filtering, point cloud sparsification by extracting model keypoints, and digital product generation: The raw 3D point cloud data obtained in the field was first converted to the CGCS2000 plane coordinate system and the 1985 National Height Datum using coordinate calculation. Then, a statistical outlier removal algorithm was applied to remove flying points, duplicate points, reflection anomalies, and outliers caused by instrument errors during the scanning process, as well as non-ground points such as vegetation, buildings, and overhead objects (power lines). Finally, high-quality raw ditch ground point cloud data was obtained for modeling by extracting model key points. This step is necessary during the topographic mapping phase of the dam design and is not an additional data processing step, thus not increasing the corresponding processing workload.

[0048] S3. Construct the original triangular network (TIN) terrain model of the gully: Using a CAD platform, construct a three-dimensional triangular network (TIN) terrain model using the Delaunay triangulation algorithm.

[0049] S4. Determine the location of the silt-trapping dam and the longitudinal gradient of the backfilling, and construct an irregular triangular network (TIN) terrain model after the dam construction: S41. Based on the selected centerline of the dam crest, determine the design dam height as 16m. Take the three-dimensional spatial coordinates of two arbitrary points on the centerline of the dam crest: P1 (422783.74, 3596619.59, 1518.50) and P2 (422910.31, 3596622.76, 1518.50). S42. According to the method in Section 8.1.2.6 of the "Design Code for Debris Flow Prevention Engineering" (T / CAGHP 021-2018), the longitudinal gradient of the sediment trap is determined to be i=65‰. S43. Assuming that the backfilling surface of the silt-retaining dam is an approximate inclined plane, the spatial coordinates of any point on the backfilling surface of the silt-retaining dam can be determined by formula (1) based on the central axis of the dam crest and the longitudinal slope of backfilling. S44. Export the original channel point cloud plane coordinates (X, Y), and automatically calculate and generate the three-dimensional coordinates (X, Y, Z) of the siltation surface of the silt-trapping dam using the tabular method according to formula (1). hy This generates point cloud data of the siltation surface after the construction of the silt-trapping dam. S45. Construct a virtual triangular network (TIN) terrain model after the construction of the silt-trapping dam using the Delaunay triangulation algorithm or the point-by-point insertion method.

[0050] S5. Based on the differences in the irregular triangular network (TIN) terrain model before and after dam construction, calculate the reservoir capacity of the silt-trapping dam, automatically generate the backfilling line, and visualize the distribution of siltation depth behind the dam (as shown in the instruction manual). Figure 3 and attached Figure 4 (as shown) S51. The volume calculation boundary is defined as the central axis of the dam crest and the entire upstream model area. The calculation field area is numbered ① (refer to the appendix in the instruction manual). Figure 3 (as shown) S52. Using the plane triangular facet of the TIN model as the basic unit, the calculation area is divided into several irregular triangular prisms. The volume of each irregular triangular prism is calculated using formula (2), and the excavation and filling volume of area ① is calculated using formula (3). The total filling volume obtained is the silt trap dam capacity of 6.02×10⁴ m³. 3 The warehouse capacity meets the design requirements; S53. Based on the original elevation and design elevation difference corresponding to each original point cloud, the boundary line where the siltation surface intersects with the original topographic surface is obtained by using a grid-based elevation difference extraction method. This automatically generates the siltation line for the silt-trapping dam reservoir area, with a siltation area of ​​10357 m². The calculated reservoir capacity diagram for this example is attached. Figure 3 As shown; S54. Based on the three-dimensional spatial elevation difference, automatically generate contour lines and color maps of the siltation thickness behind the dam (as shown in the instruction manual). Figure 4 As shown in the figure, the siltation depth ranges from 0.00 to 17.49 m, which is used to visually demonstrate the thickness and spatial distribution characteristics of debris flow deposits; S55. Output the silt trapping dam reservoir capacity calculation results and spatial visualization results in CAD format for direct use in silt trapping dam design drawings. An example is shown below: contour lines and color maps of siltation thickness within the silt trapping dam reservoir. Figure 4 As shown.

[0051] Example 5 As another preferred embodiment of the present invention, please refer to the appendix to the specification. Figure 2 As shown, this embodiment provides an iterative optimization method for the height of debris flow dams based on point cloud and TIN models, including steps S1-S5 of the debris flow dam reservoir capacity calculation method based on point cloud and TIN models described in any of the embodiments 1-3 above, and further including: S6. Calculate the design reservoir capacity of the silt trap dam obtained in step S5. With demand and storage capacity If a comparison is made, If the height of the dam is too high, then the design height of the dam should be lowered, and steps S4-S5 should be iterated. If the design height of the silt-trapping dam is too low, then the design height of the silt-trapping dam should be increased, and steps S4-S5 should be iterated until... In the formula, To meet the demand for storage capacity Storage capacity redundancy .

[0052] This embodiment organically integrates point cloud-TIN model reservoir capacity calculation, siltation feature analysis, and dam height iterative optimization into a complete technical system, completing the technical upgrade from "single reservoir capacity calculation" to "reservoir capacity-dam height collaborative design". It provides a complete technical solution for the precise and scientific design of debris flow retaining dams, filling the gap in the existing technology of lacking an integrated technical system of "precise reservoir capacity calculation-dam height iterative optimization", and promoting the development of debris flow prevention and control engineering design towards digitalization and precision.

Claims

1. A method for calculating the reservoir capacity of debris flow retaining dams based on point cloud and TIN models, characterized in that, The method includes the following steps: S1. For the selected dam site area, obtain the original ground point cloud data of the reservoir area and the surrounding set range before the construction of the dam. S2. The raw ground point cloud data obtained in step S1 is preprocessed, including point cloud data coordinate calculation, outlier removal and classification; then the preprocessed point cloud data is sparsified using the model key point extraction method. S3. Based on the point cloud data after sparsification in step S2, construct the original irregular triangular mesh terrain model of the gully ground. S4. Based on the design dam crest centerline, determine the design dam height and obtain the three-dimensional spatial coordinates (X1,Y1,Z0) and (X2,Y2,Z0) of any two points on the dam crest centerline; determine the design dam backfilling longitudinal gradient i. Treating the siltation surface of the silt-trapping dam as an approximate inclined plane, the spatial coordinates of any point on the siltation surface are determined based on the design of the dam crest centerline and the siltation longitudinal gradient i: (1)； In the formula, Z0 is the elevation of the siltation surface of the silt-retaining dam corresponding to the plane coordinates (X,Y), in meters; Z0 is the design crest elevation of the silt-retaining dam, in meters; i is the design longitudinal gradient of the siltation backfilling dam, dimensionless. Using the original point cloud planar coordinates (X,Y) in the point cloud data after the S2 step sparsification process, the three-dimensional coordinates (X,Y,Z) of the sedimentation surface of the silt-trapping dam are generated according to the above formula (1). hy The data is used to generate point cloud data of the backfill surface after the construction of the silt-trapping dam; the scope of the point cloud data of the backfill surface after the construction of the silt-trapping dam includes the dam site area and the upstream reservoir area; based on the point cloud data of the backfill surface after the construction of the silt-trapping dam, a virtual irregular triangular mesh terrain model of the dam is constructed. S5. Based on the difference between the original irregular triangular network terrain model of the gully surface and the virtual irregular triangular network terrain model after the construction of the dam, calculate the design reservoir capacity of the dam; the calculation process is as follows: S51. The boundary for volume calculation is defined as the central axis of the dam crest and the upstream reservoir area, which is divided into the calculation area. S52. Using the plane triangular face of the irregular triangular network terrain model as the basic unit, the calculation field is divided into several irregular triangular prisms. The volume of each irregular triangular prism is calculated, and the design capacity of the silt-trapping dam is calculated based on the integral method.

2. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1, characterized in that: In step S52, the volume calculation formula for the irregular triangular prism is as follows: （2）； In the formula, Let m be the volume of the j-th irregular triangular prism. 3 ; Let m be the projected area of ​​the top and bottom triangular faces of the j-th irregular triangular prism. 2 ; Let each represent the elevation of the siltation surface of the trap dam at the three vertices of the upper triangle of the j-th irregular triangular prism, in meters; Let represent the original elevations of the three vertices of the lower triangle of the j-th irregular triangular prism, in meters (m). The formula for calculating the design reservoir capacity of the silt trap dam based on the integral method is as follows: (3); where, This indicates the design capacity of the silt trap dam, in meters (m). 3 ; Let m be the volume of the j-th irregular triangular prism. 3 ; n represents the number of irregular triangular prisms; when Only positive values ​​are included in the calculation.

3. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1 or 2, characterized in that: In step S5, the original elevation Z corresponding to each original point cloud and the siltation surface elevation Z of the check dam are used. hy The elevation difference is used to extract the boundary line where the siltation surface intersects the original topographic surface using a graded extraction method based on the elevation difference grid. This boundary line is the siltation line of the silt-trapping dam reservoir area.

4. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 3, characterized in that: In step S5, based on the elevation difference in the virtual irregular triangular network terrain model after the construction of the dam, spatial visualization results are generated. The spatial visualization results include contour maps of sedimentation thickness behind the dam and color maps of sedimentation thickness, so as to intuitively show the thickness and spatial distribution characteristics of debris flow accumulation.

5. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 4, characterized in that: In step S5, the calculation results of the design reservoir capacity of the silt-trapping dam and the spatial visualization results are exported in a general engineering format. The general engineering format includes volume data tables in Excel format, backfill line maps in CAD format, and / or raster or vector data in Shapefile format, for use in engineering design or GIS platform integration.

6. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1 or 2, characterized in that: In step S4, the longitudinal gradient i of the designed sediment trap dam is determined according to the method in T / CAGHP021-2018 "Design Code for Debris Flow Prevention Engineering". The calculation formula is as follows: (3)； In the formula, i represents the longitudinal gradient of the designed silt-trapping dam. The original slope of the ditch. The internal friction angle of the debris flow.

7. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1 or 2, characterized in that: In step S1, the raw ground point cloud data is acquired using an airborne lidar scanning system, an unmanned aerial vehicle (UAV) oblique photography system, or a ground-based 3D laser scan. The sampling density of the raw ground point cloud data is 15-20 points / m. 2 The collection area covers the entire area of ​​the proposed dam site and the upstream reservoir, extending outwards by 50-100m.

8. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1 or 2, characterized in that: In step S2, when preprocessing the original ground point cloud data, the coordinates of the point cloud data are calculated, and the data is converted into a unified planar geographic coordinate system and elevation system. Filtering algorithms are used to identify noise, duplicate points, reflection anomalies, and / or anomalies caused by instrument errors during the scanning process, and non-ground points formed by vegetation, buildings, and / or suspended objects are removed. For areas with missing point cloud data, triangulation linear interpolation, Kriging interpolation, or inverse distance weighting methods are used to fill the holes.

9. The method for calculating the reservoir capacity of debris flow silt-trapping dams based on point cloud and TIN models as described in claim 1 or 2, characterized in that: In step S3, the Delaunay triangulation algorithm or point-by-point insertion method is used to construct the original irregular triangular network terrain model of the gully surface; in step S4, the Delaunay triangulation algorithm or point-by-point insertion method is used to construct the virtual irregular triangular network terrain model after the construction of the dam. The construction methods used in steps S3 and S4 are the same.

10. An iterative optimization method for the height of debris flow retaining dams based on point cloud and TIN models, characterized in that: Including steps S1-S5 of the debris flow silt retention dam capacity calculation method based on point cloud and TIN model as described in any one of claims 1-9, it further includes: S6. Calculate the design reservoir capacity of the silt trap dam obtained in step S5. With demand and storage capacity If a comparison is made, If the height of the dam is too high, then the design height of the dam should be lowered, and steps S4-S5 should be iterated. If the design height of the silt-trapping dam is too low, then the design height of the silt-trapping dam should be increased, and steps S4-S5 should be iterated until... In the formula, To meet the demand for storage capacity Storage capacity redundancy .

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