A method and system for early warning of flood disasters in open-pit mines

Abstract

The application discloses a kind of open-pit mine flood disaster early warning method and system, it is related to open-pit mine disaster early warning field, including, to open-pit mine area is scanned three-dimensionally, generates open-pit mine three-dimensional terrain data, water flow direction matrix is calculated based on D8 algorithm, and combined with GIS hydrology analysis module extraction catchment boundary line, obtain catchment area and terrain slope data;With weather station forecast data and mine area local rain gauge real-time data, calculate comprehensive prediction rainfall, obtain rainfall space-time distribution thermal map;According to open-pit mine three-dimensional terrain data and mine area geological permeability coefficient, calculate surface seepage total amount;With comprehensive prediction rainfall and surface seepage total amount.The application is input Bishop side slope stability model by water accumulation data and three-dimensional terrain, generates composite early warning signal and triggers hierarchical emergency response, realizes from data acquisition to disaster early warning whole chain accurate prediction and fast response.

Description

Technical Field

[0001] This invention relates to the field of open-pit mine disaster early warning, and in particular to a method and system for early warning of flash floods in open-pit mines. Background Technology

[0002] In the field of open-pit mine disaster early warning, flash flood disaster early warning technology has made significant progress in recent years. Traditional methods mainly rely on the combination of meteorological forecast data and static hydrological models. By collecting rainfall forecast information from meteorological stations and combining it with preset mining area topographic parameters, flood risk prediction is carried out, which improves the timeliness of early warning to a certain extent. However, its core model still uses static topographic data and homogenized hydrological parameters, and fails to fully consider the impact of dynamic topographic changes on hydrological processes during open-pit mining.

[0003] Although existing technologies have achieved basic early warning functions, there are still key technical bottlenecks. Traditional methods have significant shortcomings in multi-source data fusion and dynamic coupling analysis. Meteorological forecast data and local real-time monitoring data are usually fused with fixed weights, which is difficult to adapt to the impact of complex open-pit mine terrain on the spatial redistribution of rainfall. Seepage calculations are mostly based on saturated Darcy's law, ignoring the potential threat of water transport in unsaturated areas to slope stability. This limitation directly leads to a high false alarm rate in existing early warning systems under sudden heavy rainfall scenarios, and it is impossible to accurately predict the cumulative effect of local water accumulation on slope stability. Although existing technologies have attempted to introduce three-dimensional terrain modeling, they have not established a real-time interaction mechanism between terrain data and hydrological-mechanical coupling models, causing the early warning response to lag behind the speed of disaster development. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an early warning method for flash floods in open-pit mines, which solves the problems of insufficient early warning accuracy and delayed response caused by fixed-weight data fusion and saturated seepage assumptions in existing technologies.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a method for early warning of flash flood disasters in open-pit mines, which includes: performing a three-dimensional scan of the open-pit mine area to generate three-dimensional topographic data of the open-pit mine; calculating the water flow direction matrix based on the D8 algorithm; extracting the catchment boundary line in combination with the GIS hydrological analysis module; and obtaining the catchment area and topographic slope data.

[0008] By combining data on catchment area and topographic slope with meteorological forecast data and real-time data from local rain gauges in the mining area, a comprehensive forecast of rainfall is calculated, resulting in a heat map of the spatiotemporal distribution of rainfall.

[0009] Calculate the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area;

[0010] By comprehensively predicting rainfall and total surface infiltration, the incremental water accumulation in open pits is simulated through the water balance equation, generating a three-dimensional flood simulation animation.

[0011] The incremental water accumulation and three-dimensional topographic data of the open-pit mine are input into the Bishop slope stability model to calculate the safety factor and analyze it to obtain a composite early warning signal.

[0012] Based on the composite early warning signals, implement multi-level emergency response measures.

[0013] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: performing a three-dimensional scan of the open-pit mine area to generate three-dimensional topographic data of the open-pit mine; calculating the water flow direction matrix based on the D8 algorithm; and extracting the catchment boundary line by combining the GIS hydrological analysis module to obtain the catchment area and topographic slope data.

[0014] The open-pit mine area was scanned using an UAV-borne LiDAR, and high-precision point cloud data was obtained through GNSS / IMU combined positioning. After denoising, classification and interpolation processing, three-dimensional terrain data of the open-pit mine was generated.

[0015] Based on the three-dimensional terrain data of the open-pit mine, the Jenson-Domingue depression filling method was used to fill the depressions, and the D8 single-direction algorithm was used to calculate the water flow direction of the grid cells to obtain the water flow direction matrix encoded in 8 directions.

[0016] Based on the 8-directional encoded water flow direction matrix, the water flow accumulation is obtained by using a multi-direction accumulation method. The catchment threshold is set based on the statistical value of the minimum catchment area that actually forms surface runoff in historical rainstorm events. The catchment area is divided, and the closed boundary is extracted by the boundary tracing method to obtain the catchment boundary line.

[0017] The catchment area is obtained by accumulating the grid cells within the closed boundary using the Gaussian area algorithm based on the catchment boundary line. The elevation change rate of the grid cells and the terrain slope data are calculated using the third-order inverse distance squared difference method based on the three-dimensional terrain data of the open-pit mine.

[0018] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: combining catchment area and topographic slope data with meteorological forecast data and real-time data from local rain gauges in the mining area to calculate a comprehensive predicted rainfall amount and obtain a spatiotemporal distribution heat map of rainfall.

[0019] The Min-Max normalization method was used to standardize the catchment area, topographic slope data, meteorological forecast data and real-time data of local rain gauges in the mining area, resulting in multi-source data fused under the same dimension.

[0020] Based on the multi-source data, a dynamic weight allocation algorithm is used to calculate the gridded comprehensive predicted rainfall.

[0021] By classifying the comprehensive predicted rainfall data by intensity, a heat map of the spatiotemporal distribution of rainfall is obtained.

[0022] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: calculating the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area.

[0023] Based on borehole sampling during the geological exploration phase of the mining area, the permeability coefficient of the rock strata was determined through indoor variable head permeability tests to obtain borehole data;

[0024] Based on borehole data, inverse distance weighted interpolation is used to generate the geological permeability coefficient of the mining area;

[0025] The relative permeability is calculated based on Darcy's law, and the seepage flow rate of the grid cell is obtained by combining the hydraulic gradient and the grid area.

[0026] The infiltration flow is grouped and summed according to the catchment boundary line, and the total surface infiltration is obtained based on the real-time rainfall intensity.

[0027] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: Utilizing comprehensive predicted rainfall and total surface infiltration, the method simulates the increase in water accumulation in the open-pit mine through a water balance equation to generate a three-dimensional flood simulation animation:

[0028] The water balance equation that combines the predicted rainfall and the total surface infiltration will be used to calculate the increase in water accumulation over a given period.

[0029] Based on the three-dimensional terrain data of the open-pit mine and the time-period water accumulation increment, a dynamic mesh generation technique was adopted, and the water level rise was rendered in real time through the CesiumJS engine to obtain a three-dimensional flooding simulation animation.

[0030] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: inputting the water accumulation increment and the three-dimensional topographic data of the open-pit mine into the Bishop slope stability model, calculating the safety factor, and analyzing it to obtain a composite early warning signal:

[0031] Based on the water accumulation increment and open-pit mine 3D topographic data, the data were input into the Bishop slope stability model, and the slope safety factor was calculated using the Bishop simplified method.

[0032] Based on soil shear strength tests and historical slope stability data, a safety threshold is set.

[0033] By inverting the inundation depth of drainage units with historical flash flood events, a threshold for water accumulation increment is set.

[0034] The safety factor buffer tolerance is derived based on the standard deviation of the slope safety factor. The water accumulation increment buffer tolerance is obtained by taking the response time from the maximum theoretical drainage rate of the drainage unit to full load operation.

[0035] A red alert is triggered when the safety factor is less than the safety threshold and the increase in water accumulation is greater than the increase in water accumulation threshold.

[0036] A yellow alert is triggered when the safety factor equals the safety threshold and the increase in water accumulation equals the increase in water accumulation threshold.

[0037] A green alert is triggered when the safety factor is greater than the safety threshold and the safety factor is less than or equal to the safety threshold plus the safety factor buffer tolerance, the water accumulation increment is less than the water accumulation increment threshold and the water accumulation increment buffer tolerance is greater than or equal to the water accumulation increment threshold minus the water accumulation increment buffer tolerance.

[0038] A blue alert is triggered when the safety factor is greater than the safety threshold plus the safety factor buffer tolerance and the water accumulation increment buffer tolerance is less than the water accumulation increment threshold minus the water accumulation increment buffer tolerance.

[0039] The red, yellow, green, and blue alerts are combined into a composite warning signal.

[0040] As a preferred embodiment of the open-pit mine flash flood disaster early warning method of the present invention, the method includes the following steps: Based on the composite early warning signal, multi-level emergency response measures are implemented:

[0041] The emergency response process at the corresponding level is triggered based on the composite early warning signal;

[0042] By establishing a mapping table between early warning levels and specific emergency operations, response plans are formulated, and instruction sets are obtained and sent to the execution terminal.

[0043] Secondly, the present invention provides an early warning system for flash flood disasters in open-pit mines, including a data acquisition module that performs three-dimensional scanning of the open-pit mine area to generate three-dimensional terrain data of the open-pit mine, calculates the water flow direction matrix based on the D8 algorithm, and extracts the catchment boundary line in combination with the GIS hydrological analysis module to obtain the catchment area and terrain slope data.

[0044] The multi-source rainfall prediction fusion module combines catchment area and topographic slope data with meteorological forecast data and real-time data from local rain gauges in the mining area to calculate the comprehensive predicted rainfall and obtain a spatiotemporal distribution heat map of rainfall.

[0045] The surface seepage calculation module calculates the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area;

[0046] The 3D visualization module uses comprehensive predicted rainfall and total surface infiltration to simulate the increase in water accumulation in open pits through the water balance equation, generating a 3D flood simulation animation.

[0047] The early warning module inputs the water accumulation increment and open-pit mine three-dimensional topographic data into the Bishop slope stability model, calculates the safety factor, and analyzes it to obtain a composite early warning signal;

[0048] The emergency response execution module executes multi-level emergency response measures based on composite early warning signals.

[0049] Thirdly, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the open-pit mine flash flood disaster early warning method as described in the first aspect of the present invention.

[0050] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the open-pit mine flash flood disaster early warning method as described in the first aspect of the present invention.

[0051] The beneficial effects of this invention are as follows: high-precision three-dimensional terrain data is generated by LiDAR scanning of UAVs; water catchment characteristics are extracted based on the D8 algorithm and GIS hydrological analysis; comprehensive rainfall prediction is calculated by dynamically weighting and fusing meteorological forecasts and real-time monitoring data; then, the increase in water accumulation is accurately simulated by combining unsaturated seepage theory and water balance equation; the water accumulation data and three-dimensional terrain are input into the Bishop slope stability model to generate a composite early warning signal and trigger a graded emergency response, thus realizing accurate prediction and rapid response across the entire chain from data acquisition to disaster early warning. Attached Figure Description

[0052] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 A flowchart for early warning methods for flash floods in open-pit mines.

[0054] Figure 2 This is a schematic diagram of an early warning system for flash floods in open-pit mines.

[0055] Figure 3 This is a flowchart for 3D terrain scanning and hydrological analysis.

[0056] Figure 4This is a schematic diagram illustrating the fusion of multi-source rainfall prediction data. Detailed Implementation

[0057] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0058] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0059] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0060] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a method for early warning of flash flood disasters in open-pit mines, comprising the following steps:

[0061] S1. Perform a 3D scan of the open-pit mine area to generate 3D topographic data of the open-pit mine. Calculate the water flow direction matrix based on the D8 algorithm. Combine this with the GIS hydrological analysis module to extract the catchment boundary line and obtain the catchment area and topographic slope data.

[0062] S1.1. Use an unmanned aerial vehicle (UAV) equipped with LiDAR to scan the open-pit mine area, and obtain high-precision point cloud data through GNSS / IMU combined positioning. After denoising, classification and interpolation processing, generate three-dimensional terrain data of the open-pit mine.

[0063] Furthermore, an unmanned aerial vehicle (UAV) equipped with LiDAR was used to perform multi-flight scanning of the open-pit mine area. The flight altitude was maintained at 100 meters, with a forward overlap rate of 80% and a lateral overlap rate of 60%. GNSS real-time dynamic positioning technology was combined with an IMU inertial measurement unit for positioning, acquiring high-precision point cloud data with a planar accuracy of 0.03 meters and an elevation accuracy of 0.05 meters. Noise reduction was performed on the point cloud data using statistical filtering to remove outliers. Point cloud classification employed a cloth-like filtering algorithm to distinguish between ground and non-ground points. Three-dimensional terrain data of the open-pit mine was generated through linear interpolation of an irregular triangular network.

[0064] S1.2 Based on the three-dimensional terrain data of the open-pit mine, the Jenson-Domingue depression filling method is used to fill the depressions, and the D8 single-direction algorithm is used to calculate the water flow direction of the grid cells to obtain an 8-direction encoded water flow direction matrix.

[0065] The expression for the water flow direction in a grid cell is:

[0066] ;

[0067] in, The direction of water flow in the grid cells. This represents the current grid cell elevation value. For the first Elevation values ​​of a neighborhood The neighborhood index number, For the current grid cell to the th The horizontal distance of the neighboring grid.

[0068] Furthermore, the Jenson-Domingue depression filling method is used to process the terrain depressions, with the filling depth set to 0.01 meters to ensure unobstructed natural drainage paths. The D8 single-flow direction algorithm is used to calculate the water flow direction of each grid cell. The algorithm traverses the eight neighboring grids of each grid cell, calculates the ratio of the elevation difference between the central grid and each neighboring grid to the horizontal distance, and selects the direction with the largest ratio as the water flow direction of that grid. The output result is integer raster data, where each grid value is encoded with integers from one to eight to represent the eight directions: east, southeast, south, southwest, west, northwest, north, and northeast.

[0069] S1.3. Based on the 8-direction encoded water flow direction matrix, the water flow accumulation is obtained by using the multi-direction accumulation method. The water catchment threshold is set based on the statistical value of the minimum catchment area of ​​the actual surface runoff formed in historical rainstorm events. The catchment area is divided, and the closed boundary is extracted by the boundary tracing method to obtain the catchment boundary line.

[0070] Furthermore, a multi-flow-direction accumulation method is used to obtain the water flow accumulation of each grid cell. The water flow accumulation represents the upstream catchment area. A catchment threshold is set based on the statistical value of the minimum catchment area that actually forms surface runoff in historical rainstorm events. Areas with water flow accumulation greater than this threshold are divided into independent catchment areas. The Moore neighborhood tracking method in the boundary tracing method is used to extract the closed polygon boundary of each catchment area.

[0071] S1.4. The Gaussian area algorithm based on the catchment boundary line is used to accumulate the grid cells within the closed boundary to obtain the catchment area. Based on the three-dimensional terrain data of the open-pit mine, the elevation change rate of the grid cells and the terrain slope data are calculated using the third-order inverse distance squared difference method.

[0072] Catchment area expression:

[0073] ;

[0074] in, For the catchment area, For the first on the watershed boundary line The x-coordinates of the vertices, The total number of vertices of the catchment boundary line. For vertex index, For the first on the watershed boundary line The y-coordinates of the vertices, For the first on the watershed boundary line The y-coordinates of the vertices, For the first on the watershed boundary line The x-coordinates of each vertex.

[0075] The expression for terrain slope is:

[0076] ;

[0077] in, For terrain slope data, For the vertical elevation difference of the grid cells, The grid spacing is the vertical axis. The grid spacing is the horizontal axis. Pi is the mathematical constant of a circle.

[0078] Furthermore, the Gaussian area algorithm is used to calculate the area of ​​the closed polygon region. The algorithm traverses all vertices on the catchment boundary line, calculates the vector area formed by each vertex and the next vertex in sequence, takes the absolute value, sums them, and divides by two to obtain the catchment area. Based on the three-dimensional terrain data of the open-pit mine, the third-order inverse distance squared difference method, namely the Horn algorithm, is used to calculate the elevation change rate of each grid cell. The algorithm uses a 3x3 window to calculate the partial derivatives of elevation in the east-west and north-south directions, and obtains the slope value in degrees through the arctangent function and radian conversion. The catchment area data and terrain slope data are output.

[0079] S2. Combine the data on catchment area and topographic slope with the forecast data from the meteorological station and the real-time data from the local rain gauge in the mining area to calculate the comprehensive predicted rainfall and obtain a heat map of the spatiotemporal distribution of rainfall.

[0080] S2.1. The Min-Max normalization method is used to standardize the catchment area, topographic slope data, meteorological forecast data and real-time data of local rain gauges in the mining area to obtain multi-source data fused under the same dimension.

[0081] Furthermore, the Min-Max normalization method was used to perform a unified dimension transformation on the catchment area, topographic slope data, meteorological forecast data, and real-time data from local rain gauges in the mining area. For the catchment area data, the maximum and minimum values ​​in all grid cells were extracted, and each grid value was subtracted from the minimum value and then divided by the difference between the maximum and minimum values. The topographic slope data was processed in the same way. Since the original units of the meteorological forecast data and the real-time data from local rain gauges in the mining area were consistent, only proportional scaling was performed. Finally, a standardized multi-source dataset with all data values ​​ranging from zero to one was obtained.

[0082] S2.2 Based on the multi-source data, a dynamic weight allocation algorithm is used to calculate the gridded comprehensive predicted rainfall.

[0083] The comprehensive forecast rainfall expression is:

[0084] ;

[0085] in, In order to comprehensively predict rainfall, The weighting coefficients for meteorological forecast data. The weighting coefficients are the real-time data from local rain gauges in the mining area. This is the weighting coefficient for the terrain slope correction term. For normalized grid slope values, The gridded rainfall forecast data provided by the meteorological observatory The data is a gridded rainfall data generated from rain gauge data through Kriging interpolation.

[0086] Furthermore, based on the standardized multi-source data, a dynamic weight allocation algorithm is used to calculate the gridded comprehensive predicted rainfall. In the algorithm, the initial weight coefficient of the meteorological station forecast data is set to 0.6, the weight coefficient of the real-time data of the local rain gauge in the mining area is set to 0.3, and the weight coefficient of the terrain slope correction term is set to 0.1. When the terrain slope data is detected to exceed the threshold, the weight coefficient of the terrain slope correction term is automatically increased. At the same time, the weight allocation ratio between the meteorological station forecast data and the real-time data of the local rain gauge in the mining area is dynamically adjusted according to the degree of deviation between the two. Finally, the comprehensive predicted rainfall value of each grid unit is calculated by a weighted summation formula.

[0087] S2.3. The comprehensive predicted rainfall data is classified by intensity to obtain a heat map of the spatiotemporal distribution of rainfall.

[0088] Furthermore, the comprehensive predicted rainfall data is color-mapped according to a preset intensity level. The intensity level is divided into four intervals, each corresponding to a different color code: the lowest intensity interval is represented by blue, the medium intensity interval by green, the higher intensity interval by yellow, and the highest intensity interval by red. The color code is combined with spatial location using geographic information system software to generate a temporal and spatial distribution heat map of rainfall.

[0089] S3. Calculate the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area.

[0090] S3.1 Based on borehole sampling during the geological exploration phase of the mining area, the permeability coefficient of the rock strata was determined through indoor variable head permeability tests to obtain borehole data.

[0091] Furthermore, based on the borehole sampling data obtained during the geological exploration phase of the mining area, the permeability coefficient of each rock layer was determined by a variable head permeability test. The test process was strictly carried out in accordance with standard testing methods, and the permeability coefficient values ​​of core samples at different depths were recorded. At the same time, the planar coordinates and elevation information of the boreholes were recorded, forming a borehole dataset containing location information and lithological parameters.

[0092] S3.2. Based on borehole data, inverse distance weighted interpolation is used to generate the geological permeability coefficient of the mining area.

[0093] Furthermore, an inverse distance weighted interpolation algorithm is used to generate the geological permeability coefficient field of the mining area. The distance weight index is set to two, and the search radius is 500 meters. For each grid cell to be interpolated, its horizontal distance to the surrounding boreholes is calculated. For fault zone areas, a higher permeability coefficient value is set separately to reflect the geological structure characteristics. The output is permeability coefficient raster data with the same spatial resolution as the three-dimensional topographic data of the open-pit mine.

[0094] S3.3. Calculate the relative permeability based on Darcy's law, and obtain the seepage flow rate of the grid cell by combining the hydraulic gradient and grid area.

[0095] The expression for relative permeability is:

[0096] ;

[0097] in, This refers to relative penetration rate. For effective saturation, The shape parameter represents the pore distribution.

[0098] Furthermore, the effective saturation is calculated by the soil volumetric water content and saturated water content. The pore distribution shape parameters are determined based on lithological test data. Then, the seepage flow is calculated by combining the hydraulic gradient and grid area. The hydraulic gradient is determined by the ratio of the elevation difference of the grid cells to the horizontal distance. The grid area is the projected area of ​​the standard grid cell. The seepage flow value of each grid cell is output.

[0099] S3.4. Group and sum the grid seepage flow according to the catchment boundary line, and obtain the total surface seepage based on the real-time rainfall intensity.

[0100] The expression for the total surface seepage is:

[0101] ;

[0102] in, This represents the total surface seepage. The historical average rainfall intensity For real-time rainfall intensity, For the first The seepage flow rate of each grid cell, This represents the total number of catchment areas. For the index of the total catchment area, This represents the total number of grid cells within a single catchment area. For indexing a single catchment area, This is the attribution indicator function.

[0103] Furthermore, the catchment area number of each grid cell is determined based on the catchment boundary line. The infiltration flow of all grid cells in each catchment area is accumulated to obtain the initial total infiltration flow of each catchment area. Then, it is dynamically adjusted according to the ratio of real-time rainfall intensity to historical average rainfall intensity, and the output is the total surface infiltration flow data of each catchment area.

[0104] S4. By comprehensively predicting rainfall and total surface infiltration, the increase in water accumulation in open pits is simulated through the water balance equation, generating a three-dimensional flood simulation animation.

[0105] S4.1 Calculate the water accumulation increment during the period using the water balance equation that combines the predicted rainfall and the total surface infiltration.

[0106] Furthermore, the water balance equation is used to process the comprehensive predicted rainfall and total surface infiltration data, with a time step of fifteen minutes. The rainfall intensity change correction coefficient is determined by fitting historical data. The change in comprehensive predicted rainfall over time is calculated by dividing the difference between the rainfall in the current period and the previous period by the time step. The product of the catchment area and the comprehensive predicted rainfall is subtracted from the total surface infiltration, and then multiplied by the time step. Finally, the rainfall intensity change correction term is added, and the final output is the periodic water accumulation increment data.

[0107] S4.2 Based on the three-dimensional terrain data of the open-pit mine and the time-period water accumulation increment, dynamic mesh generation technology is adopted, and the water level rise is rendered in real time through the CesiumJS engine to obtain a three-dimensional flooding simulation animation.

[0108] Furthermore, the water level rise is calculated based on the incremental water accumulation data over a period of time. Dynamic mesh generation technology is used to refine the mesh in the waterlogged area, while the mesh in the non-waterlogged area is appropriately merged. The three-dimensional terrain data and water level data are loaded through the CesiumJS engine, and the dynamic rise of the water level is achieved by setting time axis control parameters. Color gradient effects are added to distinguish different water depth areas, and the final output is a three-dimensional flood simulation animation in WebGL format with a time dimension.

[0109] S5. Input the water accumulation increment and open-pit mine three-dimensional topographic data into the Bishop slope stability model, calculate the safety factor, and analyze it to obtain a composite early warning signal.

[0110] S5.1 Based on the water accumulation increment and open-pit mine three-dimensional topographic data, input them into the Bishop slope stability model, and use the Bishop simplified method to calculate the slope safety factor;

[0111] The expression for the slope safety factor is:

[0112] ;

[0113] in, For the slope safety factor, For the effective cohesion of the soil, The length of the smooth surface segment. For the weight of the soil strip, The angle between the tangent to the sliding surface and the horizontal plane. The effective internal friction angle of the soil.

[0114] Furthermore, based on the incremental water accumulation and the three-dimensional topographic data of the open-pit mine, the data are input into the Bishop slope stability model. When calculating the slope safety factor using the Bishop simplified method, the incremental water accumulation data is converted into pore water pressure and applied to the potential slip surface. The effective cohesion and effective internal friction angle of the soil are obtained through indoor direct shear tests. The effective cohesion of sand is taken as zero kPa, and the effective internal friction angle is taken as 30 degrees. The weight of the soil strip is calculated from the elevation value and the unit weight of the soil and rock mass in the three-dimensional topographic data of the open-pit mine. The segment length of the slip surface is determined by measuring the length of the slip arc after dividing the soil strip. The angle between the tangent of the slip surface and the horizontal plane is solved through geometric relationships. The most dangerous slip arc position is searched using an iterative method, and the ratio of the anti-slip moment to the sliding moment of each slip arc is calculated. The minimum value is taken as the slope safety factor output.

[0115] S5.2. Based on the shear strength test of soil and rock mass and historical data on slope stability, a safety threshold is set.

[0116] Furthermore, based on the effective cohesion and effective internal friction angle parameters of the soil obtained from the soil shear strength test, and combined with the critical safety factor value of landslide events recorded in the historical data of slope stability, the safety threshold is determined through statistical analysis.

[0117] S5.3 Set the threshold for water accumulation increment by inverting the inundation depth of drainage units with historical flash flood events.

[0118] Furthermore, by analyzing the design drainage capacity parameters of the drainage unit and the inundation depth data recorded in historical flash flood events, the critical values ​​of water accumulation increment corresponding to different intensity rainfall events are inverted, and the water accumulation increment threshold is set in combination with the actual operating efficiency of the drainage system.

[0119] S5.4. Based on the standard deviation of the slope safety factor, the safety factor buffer tolerance is obtained. The water accumulation increment buffer tolerance is obtained by taking the response time from the maximum theoretical drainage rate of the drainage unit to full load operation.

[0120] Furthermore, based on the uncertainty of soil and rock parameters in the slope safety factor calculation process, a large number of safety factor samples are generated through Monte Carlo simulation. Based on the standard deviation of the safety factor samples, the standard deviation is used as the safety factor buffer tolerance, which reflects the range of influence of soil and rock parameter variations on the stability assessment results.

[0121] The water accumulation increment buffer tolerance is obtained by multiplying the maximum theoretical drainage rate of the drainage unit by the response time required from startup to full-load operation. The response time of the drainage unit is obtained by measuring the time required for the drainage pump to output 90% of the design flow rate from receiving the command. The water accumulation increment buffer tolerance reflects the impact of the dynamic response capability of the drainage system on water accumulation control.

[0122] S5.5 When the safety factor is less than the safety threshold and the increase in water accumulation is greater than the increase in water accumulation threshold, a red warning is triggered.

[0123] Furthermore, during the red alert triggering phase, the slope safety factor and water accumulation increment data are monitored in real time. When the slope safety factor is less than or equal to the safety threshold and the water accumulation increment is greater than or equal to the water accumulation increment threshold, a red alert signal is immediately generated. The red alert signal includes the highest danger level indicator and emergency response instructions.

[0124] S5.6 When the safety factor equals the safety threshold and the water accumulation increment equals the water accumulation increment threshold, a yellow warning is triggered.

[0125] Furthermore, during the yellow alert triggering phase, a yellow alert signal is generated when the slope safety factor equals the safety threshold and the water accumulation increment equals the water accumulation increment threshold. The yellow alert signal includes a medium hazard level indicator and preventive action instructions.

[0126] S5.7 When the safety factor is greater than the safety threshold and the safety factor is less than or equal to the safety threshold plus the safety factor buffer tolerance, and the water accumulation increment is less than the water accumulation increment threshold and the water accumulation increment buffer tolerance is greater than or equal to the water accumulation increment threshold minus the water accumulation increment buffer tolerance, a green warning is triggered.

[0127] Furthermore, during the green warning triggering phase, when the slope safety factor is greater than the safety threshold but does not exceed the sum of the safety threshold and the safety factor buffer tolerance, and the water accumulation increment is less than the water accumulation increment threshold but not lower than the difference between the water accumulation increment threshold and the water accumulation increment buffer tolerance, a green warning signal is generated. The green warning signal indicates that a state of vigilance must be maintained.

[0128] S5.8 When the safety factor is greater than the safety threshold plus the safety factor buffer tolerance and the water accumulation increment buffer tolerance is less than the water accumulation increment threshold minus the water accumulation increment buffer tolerance, a blue warning is triggered.

[0129] Furthermore, during the blue alert triggering phase, when the slope safety factor is greater than the sum of the safety threshold and the safety factor buffer tolerance, and the water accumulation increment is less than the difference between the water accumulation increment threshold and the water accumulation increment buffer tolerance, a blue alert signal is generated, indicating that the current state is safe.

[0130] S5.9 Combine red, yellow, green and blue warnings into a composite warning signal.

[0131] Furthermore, in the stage of generating composite warning signals, red, yellow, green, and blue warning signals are integrated and processed according to warning level and spatial location to generate a standardized composite warning signal containing multi-level warning information. The composite warning signal is encapsulated and transmitted in JSON format.

[0132] S6. Implement multi-level emergency response measures based on composite early warning signals.

[0133] S6.1. Trigger the corresponding level of emergency response procedure based on composite early warning signals.

[0134] Furthermore, during the emergency response process triggering phase, based on the warning level parameters and spatial coordinate information carried in the composite warning signal, the predefined response level is automatically matched. Red warning corresponds to the highest response level, yellow warning corresponds to the intermediate response level, green warning corresponds to the primary response level, and blue warning corresponds to the basic response level. The corresponding emergency response program module is called according to the warning level parameters to complete the initialization of the response process.

[0135] S6.2 By establishing a mapping table between early warning levels and specific emergency operations, a response plan is formulated, and an instruction set is obtained and sent to the execution terminal.

[0136] Furthermore, during the response plan development phase, a pre-established mapping table between warning levels and emergency operations is used to convert the warning levels in the composite warning signals into a set of specific operational instructions. A red warning corresponds to cutting off the power supply to dangerous areas and evacuating all personnel; a yellow warning corresponds to suspending slope operations and strengthening monitoring; a green warning corresponds to restricting non-essential personnel from entering and conducting routine patrols; and a blue warning corresponds to checking equipment status. The instruction set is transmitted to the mining equipment controller and personnel positioning terminal through a standard communication protocol.

[0137] This embodiment also provides an early warning system for flash floods in open-pit mines, including: a data acquisition module that performs three-dimensional scanning of the open-pit mine area to generate three-dimensional topographic data of the open-pit mine, calculates the water flow direction matrix based on the D8 algorithm, and extracts the catchment boundary line in combination with the GIS hydrological analysis module to obtain the catchment area and topographic slope data;

[0138] The multi-source rainfall prediction fusion module combines catchment area and topographic slope data with meteorological forecast data and real-time data from local rain gauges in the mining area to calculate the comprehensive predicted rainfall and obtain a spatiotemporal distribution heat map of rainfall.

[0139] The surface seepage calculation module calculates the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area;

[0140] The 3D visualization module uses comprehensive predicted rainfall and total surface infiltration to simulate the increase in water accumulation in open pits through the water balance equation, generating a 3D flood simulation animation.

[0141] The early warning module inputs the water accumulation increment and open-pit mine three-dimensional topographic data into the Bishop slope stability model, calculates the safety factor, and analyzes it to obtain a composite early warning signal;

[0142] The emergency response execution module executes multi-level emergency response measures based on composite early warning signals.

[0143] This embodiment also provides a computer device applicable to the open-pit mine flash flood disaster early warning method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the open-pit mine flash flood disaster early warning method proposed in the above embodiment.

[0144] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0145] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for early warning of flash flood disasters in open-pit mines as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0146] In summary, this invention generates high-precision 3D terrain data through UAV LiDAR scanning, extracts water catchment characteristics based on the D8 algorithm and GIS hydrological analysis, calculates comprehensive predicted rainfall by dynamically weighting and fusing meteorological forecasts and real-time monitoring data, and then accurately simulates water accumulation increments by combining unsaturated seepage theory and water balance equations. The water accumulation data and 3D terrain are input into the Bishop slope stability model to generate a composite early warning signal and trigger a graded emergency response, thus realizing accurate prediction and rapid response across the entire chain from data acquisition to disaster early warning.

[0147] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for early warning of flash floods in open-pit mines, characterized in that: include, A 3D scan of the open-pit mine area was performed to generate 3D topographic data of the open-pit mine. The water flow direction matrix was calculated based on the D8 algorithm, and the catchment boundary line was extracted by combining the GIS hydrological analysis module to obtain the catchment area and topographic slope data. By combining data on catchment area and topographic slope with meteorological forecasts and real-time data from local rain gauges in the mining area, a comprehensive predicted rainfall amount is calculated to obtain a spatiotemporal distribution heat map of rainfall. This process includes the following steps: The Min-Max normalization method was used to standardize the catchment area, topographic slope data, meteorological forecast data and real-time data of local rain gauges in the mining area, resulting in multi-source data fused under the same dimension. Based on the multi-source data, a dynamic weight allocation algorithm is used to calculate the gridded comprehensive predicted rainfall. The comprehensive forecast rainfall expression is: ； in, In order to comprehensively predict rainfall, The weighting coefficients for meteorological forecast data. The weighting coefficients are the real-time data from local rain gauges in the mining area. This is the weighting coefficient for the terrain slope correction term. For normalized grid slope values, The gridded rainfall forecast data provided by the meteorological observatory This is a gridded rainfall data generated from rain gauge data using Kriging interpolation; By classifying the comprehensive predicted rainfall data by intensity, a heat map of the spatiotemporal distribution of rainfall is obtained; Based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area, the total surface seepage is calculated, including the following steps: Based on borehole sampling during the geological exploration phase of the mining area, the permeability coefficient of the rock strata was determined through indoor variable head permeability tests to obtain borehole data; Based on borehole data, inverse distance weighted interpolation is used to generate the geological permeability coefficient of the mining area; The relative permeability is calculated based on Darcy's law, and the seepage flow rate of the grid cell is obtained by combining the hydraulic gradient and the grid area. The expression for relative permeability is: ； in, This refers to relative penetration rate. For effective saturation, The shape parameter of the pore distribution; The infiltration flow is grouped and summed according to the catchment boundary line, and the total surface infiltration is obtained based on the real-time rainfall intensity. By comprehensively predicting rainfall and total surface infiltration, the incremental water accumulation in open pits is simulated through the water balance equation, generating a three-dimensional flood simulation animation. The following steps are included: inputting the water accumulation increment and open-pit mine three-dimensional topographic data into the Bishop slope stability model, calculating the safety factor, and analyzing it to obtain a composite early warning signal; Based on the water accumulation increment and open-pit mine three-dimensional topographic data, the data are input into the Bishop slope stability model, and the slope safety factor is calculated using the Bishop simplified method. The expression for the slope safety factor is: ； in, For the slope safety factor, For the effective cohesion of the soil, The length of the smooth surface segment. For the weight of the soil strip, The angle between the tangent to the sliding surface and the horizontal plane. The effective internal friction angle of the soil; Based on the composite early warning signals, implement multi-level emergency response measures.

2. The open-pit mine flash flood disaster early warning method as described in claim 1, characterized in that: The open-pit mine area is 3D scanned to generate 3D topographic data. The water flow direction matrix is ​​calculated based on the D8 algorithm. The catchment boundary line is extracted using a GIS hydrological analysis module to obtain the catchment area and topographic slope data. This process includes the following steps: The open-pit mine area was scanned using an UAV-borne LiDAR, and high-precision point cloud data was obtained through GNSS / IMU combined positioning. After denoising, classification and interpolation processing, three-dimensional terrain data of the open-pit mine was generated. Based on the three-dimensional terrain data of the open-pit mine, the Jenson-Domingue depression filling method was used to fill the depressions, and the D8 single-direction algorithm was used to calculate the water flow direction of the grid cells to obtain the water flow direction matrix encoded in 8 directions. Based on the 8-directional encoded water flow direction matrix, the water flow accumulation is obtained by using a multi-direction accumulation method. The catchment threshold is set based on the statistical value of the minimum catchment area that actually forms surface runoff in historical rainstorm events. The catchment area is divided, and the closed boundary is extracted by the boundary tracing method to obtain the catchment boundary line. The catchment area is obtained by accumulating the grid cells within the closed boundary using the Gaussian area algorithm based on the catchment boundary line. The elevation change rate of the grid cells and the terrain slope data are calculated using the third-order inverse distance squared difference method based on the three-dimensional terrain data of the open-pit mine.

3. The open-pit mine flash flood disaster early warning method as described in claim 1, characterized in that: By comprehensively predicting rainfall and total surface infiltration, and simulating the increase in water accumulation in open pits using the water balance equation, a three-dimensional flood simulation animation is generated, including the following steps: The water balance equation that combines the predicted rainfall and the total surface infiltration will be used to calculate the increase in water accumulation over a given period. Based on the three-dimensional terrain data of the open-pit mine and the time-period water accumulation increment, a dynamic mesh generation technique was adopted, and the water level rise was rendered in real time through the CesiumJS engine to obtain a three-dimensional flooding simulation animation.

4. The open-pit mine flash flood disaster early warning method as described in claim 1, characterized in that: Based on soil shear strength tests and historical slope stability data, a safety threshold is set. By inverting the inundation depth of drainage units with historical flash flood events, a threshold for water accumulation increment is set. The safety factor buffer tolerance is derived based on the standard deviation of the slope safety factor. The water accumulation increment buffer tolerance is obtained by taking the response time from the maximum theoretical drainage rate of the drainage unit to full load operation. A red alert is triggered when the safety factor is less than the safety threshold and the increase in water accumulation is greater than the increase in water accumulation threshold. A yellow alert is triggered when the safety factor equals the safety threshold and the increase in water accumulation equals the increase in water accumulation threshold. A green alert is triggered when the safety factor is greater than the safety threshold and the safety factor is less than or equal to the safety threshold plus the safety factor buffer tolerance, the water accumulation increment is less than the water accumulation increment threshold and the water accumulation increment buffer tolerance is greater than or equal to the water accumulation increment threshold minus the water accumulation increment buffer tolerance. A blue alert is triggered when the safety factor is greater than the safety threshold plus the safety factor buffer tolerance and the water accumulation increment buffer tolerance is less than the water accumulation increment threshold minus the water accumulation increment buffer tolerance. The red, yellow, green, and blue alerts are combined into a composite warning signal.

5. The open-pit mine flash flood disaster early warning method as described in claim 4, characterized in that: Based on the composite early warning signal, implement multi-level emergency response measures, including the following steps: The emergency response process at the corresponding level is triggered based on the composite early warning signal; By establishing a mapping table between early warning levels and specific emergency operations, response plans are formulated, and instruction sets are obtained and sent to the execution terminal.

6. An open-pit mine flash flood disaster early warning system, based on the open-pit mine flash flood disaster early warning method according to any one of claims 1 to 5, characterized in that: This includes a data acquisition module that performs 3D scanning of the open-pit mine area to generate 3D topographic data of the open-pit mine, calculates the water flow direction matrix based on the D8 algorithm, and extracts the catchment boundary line in combination with the GIS hydrological analysis module to obtain the catchment area and topographic slope data; The multi-source rainfall prediction fusion module combines catchment area and topographic slope data with meteorological forecast data and real-time data from local rain gauges in the mining area to calculate the comprehensive predicted rainfall and obtain a spatiotemporal distribution heat map of rainfall. The surface seepage calculation module calculates the total surface seepage based on the three-dimensional topographic data of the open-pit mine and the geological permeability coefficient of the mining area; The 3D visualization module uses comprehensive predicted rainfall and total surface infiltration to simulate the increase in water accumulation in open pits through the water balance equation, generating a 3D flood simulation animation. The early warning module inputs the water accumulation increment and open-pit mine three-dimensional topographic data into the Bishop slope stability model, calculates the safety factor, and analyzes it to obtain a composite early warning signal; The emergency response execution module executes multi-level emergency response measures based on composite early warning signals.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the open-pit mine flash flood disaster early warning method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the open-pit mine flash flood disaster early warning method according to any one of claims 1 to 5.

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