A method, system and storage medium for predicting a dam

Abstract

This invention provides a method, system, and storage medium for predicting landslide dams, comprising: performing terrain modeling based on terrain data of the prediction area to obtain a terrain model; determining a corresponding empirical model of landslide dam deposition morphology based on the terrain data of the prediction area; performing three-dimensional parametric modeling of the empirical model of landslide dam deposition morphology on the terrain model to obtain a three-dimensional model for landslide dam prediction; measuring the volume of the three-dimensional model for landslide dam prediction and correlating the volume with the height of the three-dimensional model for landslide dam prediction to obtain a three-dimensional model for landslide dam prediction with varying height and volume; and using the three-dimensional model for landslide dam prediction to predict landslide dams in the prediction area. This invention solves the technical problem in the prior art where the prediction methods for landslide dam morphology and height are greatly affected by terrain, leading to significant errors and making it difficult to accurately assess the hazards of landslide dams.

Description

Technical Field

[0001] This invention relates to a method, system, and storage medium for predicting landslide dams. Background Technology

[0002] Landslide dams blocking rivers are among the most dangerous geological hazards and have attracted much attention. The shape, size, height of the landslide dam, the volume of water stored in the resulting landslide-dammed lake, and water level fluctuations are crucial for predicting or assessing the hazards posed by landslide dams. Traditional methods of estimating the shape and height of landslide dams using two-dimensional cross-sections are susceptible to errors due to topographical variations, making it difficult to accurately assess the hazards. On the other hand, predictions based on traditional three-dimensional modeling are cumbersome and complex, requiring extensive model adjustments for accurate predictions, making it difficult to achieve intelligent and parameterized approaches. Summary of the Invention

[0003] To address the technical problem that existing methods for predicting the shape and height of landslide dams are subject to significant errors due to terrain influences, making it difficult to accurately assess the hazards of landslide dams, this invention provides a method, system, and storage medium for predicting landslide dams.

[0004] The embodiments of the present invention are achieved through the following technical solutions:

[0005] In a first aspect, embodiments of the present invention provide a method for predicting landslide dams, comprising:

[0006] Terrain modeling is performed based on the terrain data of the prediction area to obtain the terrain model;

[0007] Determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the predicted area;

[0008] The empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional model of the landslide dam prediction.

[0009] The volume of the predicted 3D model of the landslide dam is measured, and the volume is correlated with the height of the predicted 3D model of the landslide dam to obtain a predicted 3D model of the landslide dam with a height-volume correlation.

[0010] The landslide dam in the prediction area is predicted using the aforementioned three-dimensional landslide dam prediction model.

[0011] Furthermore, it also includes: acquiring terrain data for the prediction area.

[0012] Furthermore, the landslide dam prediction 3D model is used to predict the landslide dam in the prediction area; including:

[0013] Based on the predicted height of the landslide dam in the prediction area and the predicted three-dimensional model of the landslide dam with the relationship between the height and volume, the predicted shape and volume of the landslide dam in the prediction area are generated.

[0014] Furthermore, the empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional model for predicting the landslide dam body; including:

[0015] Determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model;

[0016] The projection points are used as modeling reference points;

[0017] The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology;

[0018] The top plane of the landslide dam is used as the reference plane;

[0019] Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

[0020] Furthermore, using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional prediction model of the landslide dam; including:

[0021] A draft empirical model of landslide dam deposition morphology is constructed, and a wedge model is formed by scanning the envelope of the draft. The wedge model is then cut using an existing terrain model to form a three-dimensional prediction model of the landslide dam located on the terrain model.

[0022] Furthermore, the prediction method is implemented using 3DEXPERIENCE software.

[0023] Secondly, embodiments of the present invention provide a landslide dam prediction system, comprising:

[0024] The terrain modeling unit is used to perform terrain modeling based on the terrain data of the prediction area to obtain a terrain model.

[0025] The empirical model determination unit is used to determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the prediction area.

[0026] The first three-dimensional modeling unit is used to perform three-dimensional parametric modeling of the empirical model of the landslide dam deposition morphology on the terrain model to obtain a three-dimensional model of the landslide dam prediction.

[0027] The second 3D modeling unit is used to measure the volume of the predicted 3D model of the landslide dam and correlate the volume with the height of the predicted 3D model of the landslide dam to obtain a predicted 3D model of the landslide dam with varying height and volume; and

[0028] The prediction unit is used to predict the landslide dam in the prediction area using the three-dimensional prediction model of the landslide dam.

[0029] Furthermore, it also includes an acquisition unit for acquiring terrain data of the prediction area.

[0030] Furthermore, the first three-dimensional modeling unit is also used to: determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model;

[0031] The projection points are used as modeling reference points;

[0032] The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology;

[0033] The top plane of the landslide dam is used as the reference plane;

[0034] Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

[0035] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing instructions that, when executed on a computer, perform the method for predicting the landslide dam.

[0036] Compared with the prior art, the embodiments of the present invention have the following advantages and beneficial effects:

[0037] This invention discloses a method, system, and storage medium for predicting landslide dams. The method involves: creating a terrain model based on terrain data of the prediction area; determining a corresponding empirical model of landslide dam deposition morphology based on the terrain data; performing three-dimensional parametric modeling of the empirical model on the terrain model to obtain a three-dimensional landslide dam prediction model; measuring the volume of the three-dimensional landslide dam prediction model and correlating the volume with its height to obtain a three-dimensional landslide dam prediction model showing a change in height-volume relationship; and using this three-dimensional landslide dam prediction model to predict landslide dams in the prediction area. This solves the technical problem in existing methods for predicting landslide dam morphology and height that are significantly affected by terrain, making it difficult to accurately assess the hazards of landslide dams. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart illustrating the method for predicting landslide dams.

[0040] Figure 2 This is a schematic diagram of the structure of the landslide dam prediction system.

[0041] Figure 3 A schematic diagram of the structure for terrain modeling in 3DEXPERIENCE software.

[0042] Figure 4 A schematic diagram of a terrain modeling structure with modeling reference points in 3DEXPERIENCE software.

[0043] Figure 5 This is a schematic diagram of a terrain modeling structure with modeling reference points and modeling reference surfaces in 3DEXPERIENCE software.

[0044] Figure 6 A schematic diagram of the terrain modeling structure for constructing an empirical model of the landslide dam accumulation morphology in 3DEXPERIENCE software.

[0045] Figure 7 For 3DEXPERIENCE software Figure 6 A schematic diagram of the three-dimensional model structure of the landslide dam predicted after the sketched envelope is used to form a wedge model.

[0046] Figure 8 To measure using the volume measurement tool in 3DEXPERIENCE software Figure 7 A schematic diagram of the structure of the three-dimensional model for predicting the volume of a landslide dam.

[0047] Figure 9 This is a schematic diagram of the landslide dam prediction model structure in 3DEXPERIENCE software, which correlates the measured volume with the height of the landslide dam. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of this invention are only for explaining this invention and are not intended to limit this invention.

[0049] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be apparent to those skilled in the art that these specific details are not necessary to practice the invention. In other embodiments, well-known structures, circuits, materials, or methods have not been specifically described in order to avoid obscuring the invention.

[0050] Throughout this specification, references to "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with that embodiment or example is included in at least one embodiment of the invention. Therefore, the phrases "an embodiment," "an example," "an example," or "an example" appearing in various places throughout the specification do not necessarily refer to the same embodiment or example. Furthermore, specific features, structures, or characteristics can be combined in one or more embodiments or examples in any suitable combination and / or sub-combination. Moreover, those skilled in the art will understand that the illustrations provided herein are for illustrative purposes and are not necessarily drawn to scale. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0051] In the description of this invention, the terms "front", "rear", "left", "right", "up", "down", "vertical", "horizontal", "high", "low", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting the scope of protection of this invention.

[0052] Example

[0053] To address the technical problem that existing methods for predicting the shape and height of landslide dams are subject to significant errors due to terrain influences, making it difficult to accurately assess the hazards of landslide dams, this invention provides a method, system, and storage medium for predicting landslide dams.

[0054] In a first aspect, embodiments of the present invention provide a method for predicting landslide dams, referring to... Figure 1 As shown, it includes:

[0055] S1. Based on the terrain data of the prediction area, perform terrain modeling to obtain the terrain model;

[0056] S2. Determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the predicted area;

[0057] S3. The empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional model of the landslide dam prediction.

[0058] S4. Measure the volume of the three-dimensional model of the landslide dam prediction, and correlate the volume with the height of the three-dimensional model of the landslide dam prediction to obtain a three-dimensional model of the landslide dam prediction with a height-volume correlation.

[0059] S5. Use the three-dimensional model of the dam body prediction to predict the dam body in the prediction area.

[0060] The method of this invention can be executed on a server or client. Optionally, the method can be implemented using 3DEXPERIENCE software.

[0061] Therefore, this embodiment of the invention obtains a terrain model by performing terrain modeling based on the terrain data of the prediction area; determines the corresponding empirical model of landslide dam deposition morphology based on the terrain data of the prediction area; performs three-dimensional parametric modeling of the empirical model of landslide dam deposition morphology on the terrain model to obtain a three-dimensional model of landslide dam prediction; measures the volume of the three-dimensional model of landslide dam prediction and correlates the volume with the height of the three-dimensional model of landslide dam prediction to obtain a three-dimensional model of landslide dam prediction with varying height and volume; and uses the three-dimensional model of landslide dam prediction to predict landslide dams in the prediction area, thus solving the technical problem in the prior art where the prediction methods for landslide dam morphology and height are greatly affected by terrain, making it difficult to accurately assess the hazards of landslide dams.

[0062] Furthermore, it also includes: acquiring terrain data for the prediction area.

[0063] Furthermore, the landslide dam prediction 3D model is used to predict the landslide dam in the prediction area; including:

[0064] Based on the predicted height of the landslide dam in the prediction area and the predicted three-dimensional model of the landslide dam with the relationship between the height and volume, the predicted shape and volume of the landslide dam in the prediction area are generated.

[0065] Furthermore, the empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional model for predicting the landslide dam body; including:

[0066] Determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model;

[0067] The projection points are used as modeling reference points;

[0068] The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology;

[0069] The top plane of the landslide dam is used as the reference plane;

[0070] Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

[0071] Furthermore, using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional prediction model of the landslide dam; including:

[0072] A draft empirical model of landslide dam deposition morphology is constructed, and a wedge model is formed by scanning the envelope of the draft. The wedge model is then cut using an existing terrain model to form a three-dimensional prediction model of the landslide dam located on the terrain model.

[0073] Furthermore, the prediction method is implemented using 3DEXPERIENCE software.

[0074] An exemplary method for predicting landslide dams includes the following steps:

[0075] ①For example Figure 3 As shown, a three-dimensional geological model of the landslide dam prediction area was established, and terrain modeling was performed in 3DEXPERIENCE software based on the terrain data measured by UAV.

[0076] ②For example Figure 4 As shown, the projection point of the modeling center point of the landslide dam body on the terrain is determined, and this point is used as the modeling reference point; Figure 4 and Figure 5 In the figure, “X” represents the modeling reference point.

[0077] ③ For example Figure 5 As shown, the position of the top plane of the landslide dam is determined by the reference point and the height of the landslide dam, and the top plane of the landslide dam is used as the modeling reference plane. The distance from the reference point to the reference plane is the height of the predicted model of the landslide dam.

[0078] ④ For example Figure 6 As shown, an empirical model of the landslide dam deposition morphology was determined and a modeling sketch was constructed. Taking the deposition morphology of the landslide dams in the "10.11" and "11.03" incidents in Baige as examples, the bottom of the landslide dam is the terrain where the original riverbed connects with the slopes on both banks. The transverse slope ratio is that the top surface is nearly horizontal in the transverse direction, and the longitudinal slope ratio is 1:4 upstream and 1:5 downstream. The top surface of the landslide dam connects with the two slopes in the transverse direction, and the longitudinal length is about 230m.

[0079] ⑤ For example Figure 7 As shown, the established sketch is scanned to form a wedge model, and the wedge is cut with the existing terrain to form a 3D model of the landslide dam predicted above the terrain.

[0080] ⑥ For example Figure 8 As shown, the volume of the predicted three-dimensional model of the landslide dam was measured using the volume measurement tool in 3DEXPERIENCE software.

[0081] ⑦ For example Figure 9 As shown, a predictive model is used to correlate the measured volume with the height of the landslide dam, thereby adjusting the relationship between the landslide dam height and the volume of the landslide dam.

[0082] The entire modeling process must be based on reference points and reference surfaces. All modeling sketches and model components must be associated with reference points and reference surfaces. The landslide dam model must be generalized in a regular way to achieve parametric association.

[0083] Therefore, the embodiments of the present invention can use 3DEXPERIENCE software to predict the height of a landslide dam, automatically generate a landslide dam prediction model, and automatically calculate its shape and volume.

[0084] Therefore, the embodiments of the present invention can solve the problems of inaccurate measurement, long time consumption, and difficulty in parameterization in the prediction of landslide dams.

[0085] This invention utilizes 3DEXPERIENCE software for parametric modeling and prediction of landslide dams. First, the topographic data of the prediction area is determined, and topographic modeling is performed in 3DEXPERIENCE based on UAV-measured topographic data. Second, an empirical model of the landslide dam deposition morphology is determined. Taking the deposition morphology of the Baige landslides on October 11th and November 3rd as examples, the bottom of the landslide dam is the original riverbed connecting with the slopes on both banks; the transverse slope ratio is nearly horizontal at the top; the longitudinal slope ratio is 1:4 upstream and 1:5 downstream; the top of the dam connects transversely with the two slopes, and its longitudinal length is approximately 230m. Third, a three-dimensional parametric model of the landslide deposition morphology is performed on the established topography. To achieve parametric modeling, parametric association of each modeling component and process is required. The top center point of the landslide dam is used as the reference point, the top platform plane as the reference plane, and the distance from the reference point to the reference plane is the height of the landslide dam, thus establishing the landslide dam model. A predictive model is developed by measuring the volume of a landslide dam and correlating the measured volume with the height of the landslide dam, thereby adjusting the relationship between the landslide dam height and the volume of the landslide dam.

[0086] For example, the Baige landslide, after two landslides on October 11 and November 3, 2018, has posed a significant threat to the upstream Boluo Hydropower Station and the downstream Yebatan Hydropower Station. Based on the deformation and failure characteristics and stability analysis results of the Baige landslide remnants, this paper analyzes the landslide remnant landslide ...

[0087] Using the landslide damming morphology and material composition characteristics of the Baige landslides on October 11th and November 3rd as a solid model, and combining the instability mode combination of the Baige landslide remnants with the riverbed topography characteristics after the November 3rd dam break, the boundary conditions of the landslide damming morphology model are proposed. The morphology model parameters are as follows:

[0088] Riverbed: After the landslide dam was released on November 3, the river channel narrowed. According to the topographic map measured by the Chengdu Institute after the dam broke on November 14, 2018, the water surface width was 100-150m and the water surface elevation was 2905m. Compared with the topographic map measured by the China Institute of Water Resources and Hydropower Research in April 2019, the valley topography did not change much. The volume change of the valley topography below 2950m was less than 1%, and the riverbed water surface elevation changed slightly due to different flow rates.

[0089] The transverse slope ratio of the landslide dam deposit: Based on the transverse morphological characteristics of the landslide deposits in October 11 and November 3, and referring to the deposit morphology of similar landslide dams, including the Tangjiashan landslide dam, the transverse slope ratio of the top surface of the landslide dam deposit is proposed to be nearly horizontal.

[0090] Upstream and downstream slope ratios of the landslide dam: Based on the morphological characteristics of the landslide dams in the "10.11" and "11.03" events, and referring to the morphological characteristics of similar landslide dams, including the Tangjiashan landslide dam, the upstream slope ratio of the landslide dam is 1:4, and the downstream slope ratio is 1:5.

[0091] Loose volume coefficient of the landslide dammed deposit: The original rock of the landslide is gray-green serpentinite, gneiss interbedded with sericite quartz schist and bimcite quartz schist and marble. By engineering analogy, the comprehensive dry density is about 2.55 g / cm3. The material composition of the landslide dammed deposit is mainly composed of isolated boulders, with some local boulders and soil. This landslide is a high-altitude landslide with a height difference of 500-700m. The landslide instability impact force is large, and the structure is relatively compact. According to the field physical property test data of the Institute of Water Resources and Hydropower Research, the dry density of the deposit is about 2.35 g / cm3, thus the loose volume coefficient is 1.1.

[0092] Based on the measured topography of the Baige landslide area in 2021, the predicted riverbed elevation of the landslide dam center is 2886m. To analyze the impact of the landslide-induced rise in the Jinsha River water level on the power generation of the Boluo Hydropower Station, the following elevations were used: 2899.7m (landslide dam height 13.7m), 2908.2m (landslide dam height 22.2m), 2914.5m (landslide dam height 28.5m), and 2917.1m (landslide dam height 31.1m). Based on parametric predictions using 3DEXPERIENCE software, the calculated landslide dam volume is 253,000 m³, calculated at elevations of 2920.1m (landslide dam height 34.1m), 2925.0m (landslide dam height 39.0m), 2928.6m (landslide dam height 42.6m), and 2935.7m (landslide dam height 49.7m). 3 605,000 m 3 935,000 m 3 1.1 million m 3 1.353 million m 3 1.837 million m 32.233 million m 3 3.168 million m 3 .

[0093] The current plan is to excavate 1.28 million cubic meters of riverbed without changing the riverbed bottom elevation of 2886m. 3 Widening the riverbed will reduce the impact of potential landslides and dams on upstream and downstream hydropower stations. The elevation of the pass at the top of the landslide dam was calculated using the same volume of landslide dam accumulation after widening the terrain. The resulting elevations of the passes are as follows: 2891.9m (landslide dam height 5.9m), 2901.4m (landslide dam height 15.4m), 2906.4m (landslide dam height 20.4m), 2908.9m (landslide dam height 22.9m), 2912.0m (landslide dam height 26.0m), 2917.1m (landslide dam height 31.1m), 2920.9m (landslide dam height 34.9m), and 2928.4m (landslide dam height 42.4m).

[0094] Secondly, embodiments of the present invention provide a prediction system for landslide dams, referring to... Figure 2 As shown, it includes:

[0095] The terrain modeling unit is used to perform terrain modeling based on the terrain data of the prediction area to obtain a terrain model.

[0096] The empirical model determination unit is used to determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the prediction area.

[0097] The first three-dimensional modeling unit is used to perform three-dimensional parametric modeling of the empirical model of the landslide dam deposition morphology on the terrain model to obtain a three-dimensional model of the landslide dam prediction.

[0098] The second 3D modeling unit is used to measure the volume of the predicted 3D model of the landslide dam and correlate the volume with the height of the predicted 3D model of the landslide dam to obtain a predicted 3D model of the landslide dam with varying height and volume; and

[0099] The prediction unit is used to predict the landslide dam in the prediction area using the three-dimensional prediction model of the landslide dam.

[0100] Furthermore, it also includes an acquisition unit for acquiring terrain data of the prediction area.

[0101] Furthermore, the first three-dimensional modeling unit is also used to: determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model;

[0102] The projection points are used as modeling reference points;

[0103] The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology;

[0104] The top plane of the landslide dam is used as the reference plane;

[0105] Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

[0106] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing instructions that, when executed on a computer, perform the method for predicting the landslide dam.

[0107] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method of predicting a dam, characterized by, include: Terrain modeling is performed based on the terrain data of the prediction area to obtain the terrain model; Determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the predicted area; The empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain a three-dimensional model of the landslide dam prediction. The volume of the predicted 3D model of the landslide dam is measured, and the volume is correlated with the height of the predicted 3D model of the landslide dam to obtain a predicted 3D model of the landslide dam with a height-volume correlation. The landslide dam prediction 3D model is used to predict the landslide dam in the prediction area; The modeling methods for predicting the three-dimensional model of a landslide dam include: Determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model; The projection points are used as modeling reference points; The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology; The top plane of the landslide dam is used as the reference plane; Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

2. The method of predicting damming according to claim 1, wherein Also includes: Obtain terrain data for the prediction area.

3. The method of predicting damming according to claim 1, wherein The landslide dam prediction three-dimensional model is used to predict the landslide dam in the prediction area; including: Based on the predicted height of the landslide dam in the prediction area and the predicted three-dimensional model of the landslide dam with the relationship between the height and volume, the predicted shape and volume of the landslide dam in the prediction area are generated.

4. The method of predicting damming according to claim 1, wherein Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam deposition morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam; including: A draft empirical model of landslide dam deposition morphology is constructed, and a wedge model is formed by scanning the envelope of the draft. The wedge model is then cut using an existing terrain model to form a three-dimensional prediction model of the landslide dam located on the terrain model.

5. The method for predicting landslide dams as described in any one of claims 1-3, characterized in that, The prediction method is implemented using 3DEXPERIENCE software.

6. A prediction system for landslide dams, characterized in that, include: The terrain modeling unit is used to perform terrain modeling based on the terrain data of the prediction area to obtain a terrain model. The empirical model determination unit is used to determine the corresponding empirical model of landslide dam deposition morphology based on the topographic data of the prediction area. The first three-dimensional modeling unit is used to perform three-dimensional parametric modeling of the empirical model of the landslide dam deposition morphology on the terrain model to obtain a three-dimensional model of the landslide dam prediction. The second 3D modeling unit is used to measure the volume of the predicted 3D model of the landslide dam and correlate the volume with the height of the predicted 3D model of the landslide dam to obtain a predicted 3D model of the landslide dam with varying height and volume; and The prediction unit is used to predict the landslide dam in the prediction area using the three-dimensional prediction model of the landslide dam. The first three-dimensional model modeling unit is also used to: determine the projection point of the center point of the empirical model of the landslide dam deposition morphology onto the terrain model; The projection points are used as modeling reference points; The top plane position of the landslide dam is determined by the benchmark point and the height of the landslide dam body in the empirical model of landslide dam accumulation morphology; The top plane of the landslide dam is used as the reference plane; Using the distance from the reference point to the reference surface as the height of the landslide dam prediction model, the empirical model of the landslide dam accumulation morphology is used to perform three-dimensional parametric modeling on the terrain model to obtain the three-dimensional prediction model of the landslide dam.

7. The landslide dam prediction system as described in claim 6, characterized in that, It also includes an acquisition unit for acquiring terrain data of the prediction area.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, perform the landslide dam prediction method as described in any one of claims 1-4.

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