A landslide and debris flow disaster chain hazard detection method and system

Abstract

The present application provides a method and system for detecting the danger of a landslide and debris flow disaster chain, comprising: acquiring DEM data of a target detection area, dividing the target detection area into a number of watershed units; constructing an indicator system for a landslide and debris flow disaster chain, wherein the indicator system for a landslide and debris flow disaster chain includes terrain indicators, material source indicators, and hydrodynamic indicators; calculating the terrain indicators and material source indicators corresponding to the watershed units, and performing graded assignments respectively; calculating the susceptibility index of landslide and debris flow disasters of the watershed units using a comprehensive index method based on the terrain indicators and the material source indicators; calculating the hydrodynamic indicators corresponding to the watershed units, and performing graded assignments; calculating the danger index of landslide and debris flow disasters of the watershed units based on the susceptibility index and the hydrodynamic indicators. The present application can effectively improve the accuracy and reliability of the detection results of landslide and debris flow disasters.

Description

Technical Field

[0001] The present application relates to the field of disaster geology, and in particular to a method and system for detecting the danger of landslide and debris flow disaster chains. Background Art

[0002] Landslides and debris flows are two common and extremely dangerous geological hazards in mountainous areas. This is particularly true of the direct-conversion landslide-debris flow hazard chain, where, under certain conditions, a landslide, after initiation, directly transforms into a debris flow without stagnating. This hazard chain arises from changes in the composition of the landslide during its movement, which alters the physical and mechanical properties of the water-soil mixture and ultimately transforms into a debris flow. The amplifying effect of the interaction between landslides and debris flows poses a greater threat to hazard-bearing structures within the affected area.

[0003] In recent years, with the continuous increase in infrastructure construction in mountainous areas, the safety issues caused by mountain disasters (chains) have gradually become the focus of attention in academia and engineering circles. Scientific detection of the dangers of landslide-mudslide disaster chains is of great significance.

[0004] However, existing debris flow detection methods lack mature and comprehensive landslide-debris flow disaster detection methods and indicator systems, which leads to the neglect of the coupling mechanism between landslides and debris flows and the cumulative amplification effect between the two, making the detection data incomplete, resulting in low accuracy and reliability of the detection results of landslide and debris flow disasters in the target detection area. Summary of the Invention

[0005] In response to the problems in the prior art, the present application provides a landslide and debris flow hazard chain hazard detection method and system with a mature landslide and debris flow hazard chain indicator system, which can improve the accuracy and reliability of landslide and debris flow disaster detection results.

[0006] A method for detecting the danger of a landslide and debris flow disaster chain comprises the following steps:

[0007] Obtain the DEM data of the target detection area and divide the target detection area into several watershed units;

[0008] Constructing a landslide and debris flow disaster chain indicator system, wherein the landslide and debris flow disaster chain indicator system includes terrain indicators, material source indicators and hydrodynamic indicators;

[0009] Calculating the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit, and assigning a graded value to the terrain index;

[0010] Obtaining landslide hazard susceptibility zoning data, historical borehole cataloging data, and current borehole cataloging data of the target detection area, calculating the material source index corresponding to the watershed unit, and assigning grades to the material source index;

[0011] Calculating the susceptibility index of landslide and debris flow disasters of the watershed unit by using a comprehensive index method according to the terrain index and the material source index;

[0012] Obtaining rainfall station data of the target detection area, calculating the hydrodynamic index corresponding to the watershed unit, and assigning grades to the hydrodynamic index;

[0013] The hazard index of landslide and debris flow disasters in the watershed unit is calculated according to the susceptibility index and the hydrodynamic index.

[0014] The present application also provides a landslide and debris flow disaster chain hazard detection system, comprising:

[0015] Watershed unit segmentation module: used to obtain DEM data of the target detection area and divide the target detection area into several watershed units;

[0016] Landslide and debris flow disaster chain indicator system construction module: used to construct a landslide and debris flow disaster chain indicator system, wherein the landslide and debris flow disaster chain indicator system includes terrain indicators, material source indicators and hydrodynamic indicators;

[0017] A terrain index calculation module is used to calculate the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit, and to grade and assign values ​​to the terrain index;

[0018] Material source index calculation module: obtains the landslide hazard susceptibility zoning data, historical borehole catalog data and current borehole catalog data of the target detection area, calculates the material source index corresponding to the watershed unit, and assigns graded values ​​to the material source index;

[0019] Susceptibility index calculation module: used for calculating the susceptibility index of landslide and debris flow disasters of the watershed unit by using a comprehensive index method according to the terrain index and the material source index;

[0020] A hydrodynamic index calculation module is used to obtain rainfall station data in the target detection area, calculate the hydrodynamic index corresponding to the watershed unit, and assign grades to the hydrodynamic index;

[0021] Hazard index calculation module: used to calculate the hazard index of landslide and debris flow disasters in the basin unit based on the susceptibility index and the hydrodynamic index.

[0022] Compared with existing technologies, this solution selects areas where the evolution type of landslides and debris flows is a direct conversion type as the detection object, fully considering their development characteristics, in order to construct a highly targeted landslide and debris flow disaster chain indicator system including terrain indicators, material source indicators and hydrodynamic indicators. In addition, the material source indicators fully consider the cumulative amplification and along-the-path amplification effects of the landslide-debris flow disaster chain, and include the accumulation bodies produced by landslides and debris flows in the upstream small watershed into the debris flow material source of the downstream small watershed, thereby improving the accuracy of the detection results of the susceptibility of landslide and debris flow disasters in the detection area. In addition, heavy rainfall is the most important inducing factor for the outbreak of the landslide-debris flow disaster chain. Combining the hydrodynamic indicators and the susceptibility detection results of landslide and debris flow disasters can effectively improve the accuracy and reliability of the detection results of the danger of the landslide and debris flow disaster chain in the detection area.

[0023] In order to provide a clearer understanding of the present application, the specific implementation methods of the present application will be described below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of a method for detecting the danger of a landslide and debris flow disaster chain is provided for this application;

[0025] Figure 2 A flow chart of a method for segmenting watershed units in a landslide and debris flow hazard chain detection method for this application;

[0026] Figure 3 A flow chart of a method for calculating terrain indicators for a landslide and debris flow hazard chain detection method for this application;

[0027] Figure 4 A flow chart of a method for calculating source indicators for a landslide and debris flow hazard chain detection method in this application;

[0028] Figure 5 This is a flow chart of a method for grading and assigning values ​​of terrain indicators and material source indicators for a landslide and debris flow hazard chain detection method in this application;

[0029] Figure 6 A flow chart of a method for evaluating the accuracy of a susceptibility index of a landslide and debris flow hazard chain detection method in this application;

[0030] Figure 7 This is a flow chart of a method for assigning hydrodynamic index classification values ​​to a landslide and debris flow hazard chain detection method in this application;

[0031] Figure 8 This is a schematic diagram of a landslide and debris flow disaster chain hazard detection system for this application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0033] It should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations in the flowcharts may be implemented out of sequence, and steps that do not have a logical contextual relationship may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the contents of this application, may add one or more other operations to the flowcharts, or may remove one or more operations from the flowcharts.

[0034] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0035] Example 1

[0036] See also Figure 1 , Figure 1 This is a flow chart of a method for detecting the danger of a landslide and debris flow disaster chain. This application provides a method for detecting the danger of a landslide and debris flow disaster chain, which specifically includes the following steps:

[0037] S1: Obtain the DEM data of the target detection area and divide the target detection area into several watershed units;

[0038] S2: Constructing a landslide and debris flow disaster chain indicator system, wherein the landslide and debris flow disaster chain indicator system includes terrain indicators, material source indicators, and hydrodynamic indicators;

[0039] S3: Calculating the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit, and assigning a graded value to the terrain index;

[0040] S4: Obtaining landslide hazard susceptibility zoning data, historical borehole catalog data, and current borehole catalog data of the target detection area, calculating the material source index corresponding to the watershed unit, and assigning grades to the material source index;

[0041] S5: Calculating the susceptibility index of landslide and debris flow disasters of the watershed unit using a comprehensive index method based on the terrain index and the material source index;

[0042] S6: Obtaining rainfall station data of the target detection area, calculating the hydrodynamic index corresponding to the watershed unit, and assigning grades to the hydrodynamic index;

[0043] S7: Calculate the risk index of landslide and debris flow disasters of the watershed unit according to the susceptibility index and the hydrodynamic index.

[0044] Compared with existing technologies, this solution selects areas where the evolution type of landslides and debris flows is a direct conversion type as the detection object, fully considering their development characteristics, in order to construct a highly targeted landslide and debris flow disaster chain indicator system including terrain indicators, material source indicators and hydrodynamic indicators. In addition, the material source indicators fully consider the cumulative amplification and along-the-path amplification effects of the landslide-debris flow disaster chain, and include the accumulation bodies produced by landslides and debris flows in the upstream small watershed into the debris flow material source of the downstream small watershed, thereby improving the accuracy of the detection results of the susceptibility of landslide and debris flow disasters in the detection area. In addition, heavy rainfall is the most important inducing factor for the outbreak of the landslide-debris flow disaster chain. Combining the hydrodynamic indicators and the susceptibility detection results of landslide and debris flow disasters can effectively improve the accuracy and reliability of the detection results of the landslide and debris flow disaster chain danger in the detection area.

[0045] For step S1: obtain DEM data of the target detection area and divide the target detection area into several watershed units.

[0046] Among them, by obtaining historical landslide and debris flow disaster chain data of several detection areas, the distribution characteristics and laws of historical landslide and debris flow in the detection areas are analyzed, and the detection areas where the landslide and debris flow disaster chain evolution type is direct conversion type are determined as target detection areas.

[0047] The landslide and debris flow hazard chain evolution types include direct transformation and indirect transformation. The direct transformation type refers to a hazard chain model in which, after the original slope becomes unstable and forms a sliding body, it continues to move without stopping or accumulating. As the material composition of the sliding body changes during movement, the physical and mechanical properties of the water-soil mixture change accordingly, and ultimately directly evolve into a debris flow. The indirect transformation type refers to a hazard chain model in which, after the original slope becomes unstable and forms a sliding body, it accumulates in the channel to form a quasi-debris flow, which then moves again and evolves into a debris flow under the influence of subsequent rainfall, runoff, and erosion.

[0048] The historical landslide and debris flow disaster chain data includes multi-dimensional data such as field geological disaster surveys, optical satellite and spaceborne radar remote sensing, drone or aerial imagery, ground-based lidar, and surface and deep underground deformation and displacement measurements. The historical landslide and debris flow disaster chain data can be downloaded from the geological disaster data published on the websites of geological departments or geological research institutions, or obtained through detailed on-site geological disaster surveys.

[0049] Based on the topography, meteorological conditions, and geological structure of the historical landslide and debris flow disaster chain data, a comprehensive analysis is conducted on the disaster scale and distribution, slope geological structure, and landslide and debris flow disaster chain characteristics of the detection area to determine the landslide and debris flow disaster chain evolution type of the detection area, wherein the meteorological conditions are mainly rainfall data. In this embodiment, the detection area where landslide and debris flow disasters appear in multiple clusters and belts in space, with a high degree of density, multiple landslides in the same basin sliding and liquefying at the same time, landslides converge along valleys to form debris flows, and the contact zone between the loose accumulation layer on the upper slope and the hard bedrock below is prone to forming a seepage slip zone is identified as the target detection area for the landslide and debris flow disaster chain evolution type of direct conversion.

[0050] The Digital Elevation Model (DEM) data is a digital simulation of landforms and topography achieved through limited terrain elevation data, and can be obtained by downloading from a geospatial data cloud.

[0051] See also Figure 2 , Figure 2 This is a flow chart of a method for segmenting watershed units in a landslide and debris flow hazard chain detection method of this application. The method of obtaining DEM data of the target detection area and segmenting the target detection area into several watershed units also includes the following steps:

[0052] S11: performing flow direction analysis on the target detection area according to the DEM data to obtain water flow direction data of the target detection area;

[0053] S12: Calculating the cumulative amount of confluence according to the water flow direction data;

[0054] S13: dividing the target detection area into a plurality of watershed units according to the accumulated flow volume;

[0055] S14: Manually adjust the watershed unit.

[0056] In this embodiment, for steps S11-S14, the DEM data is loaded into GIS software. Based on the DEM data, the GIS software's flow direction tool is used to obtain water flow direction data. The GIS software's cumulative runoff tool is used to calculate the cumulative runoff based on the water flow direction data. Based on the cumulative runoff, the GIS software's watershed tool is used to segment the target detection area into a number of watershed units. The GIS software's editing tools are used to manually inspect and adjust the watershed units.

[0057] Among them, the geographic information system software can be ArcGIS software, and the manual adjustment of the watershed unit includes: merging, splitting and moving the boundaries of the watershed unit, so that each of the watershed units contains a complete debris flow formation area, accumulation area and flow area, as well as the area where collapse and landslide disasters occurring along the debris flow supply the debris flow.

[0058] Of course, in other embodiments, other Geographic Information System (GIS) software may be used based on the DEM data to divide the target detection area into a number of watershed units.

[0059] Regarding step S2: constructing a landslide and debris flow disaster chain index system, wherein the landslide and debris flow disaster chain index system includes terrain indicators, material source indicators and hydrodynamic indicators.

[0060] Among them, the terrain indicators include: watershed area, main ditch length, watershed relative elevation difference, channel curvature and watershed cutting density. The watershed area affects the water collection capacity of the target detection area. The larger the watershed area, the more water the target detection area collects per unit time, and the greater the susceptibility to landslide and debris flow disasters. The main ditch length affects the drainage area and river length of the target detection area. The longer the main ditch is, the more runoff water the target detection area can accommodate, providing powerful hydrodynamic conditions for debris flow, and the greater the susceptibility to landslide and debris flow disasters. The watershed relative elevation difference refers to the difference between the altitude of the highest point and the altitude of the lowest point in a watershed. It is the bed condition for the conversion of potential energy into kinetic energy of debris flow fluid in the target detection area. The larger the watershed relative elevation difference, the greater the kinetic energy of the debris flow fluid, and the greater the susceptibility to landslide and debris flow disasters. The channel curvature refers to the ratio of the main channel length to the main channel straight length, which affects the flow characteristics of debris flow in the target detection area. The greater the channel curvature, the more likely the debris flow in the target detection area will form flow bursts, and the greater the susceptibility to landslide and debris flow disasters. The watershed incision density refers to the ratio of the total length of the water system in the target detection area to the watershed area, which affects the slope stability of the target detection area. The greater the watershed incision density, the weaker the slope stability of the target detection area and the greater the susceptibility to landslide and debris flow disasters.

[0061] The material source indicators include: the average thickness of loose materials in the sand-producing area, the reserves of loose materials along the gully, and the ratio of the length of the sediment supply section. The average thickness of loose materials in the sand-producing area refers to the thickness of loose materials such as soil, sand, and gravel on the surface of the target detection area, reflecting the scope and amount of loose solid material supply in the target detection area, thereby affecting the scale of debris flow. The greater the average thickness of loose materials in the sand-producing area, the larger the scale of debris flow in the target detection area, and the greater the risk of landslide and debris flow disasters. The reserves of loose materials along the gully refer to the total amount of unstable solid materials distributed along the gully in the target detection area that may participate in the formation of geological disasters such as debris flow. It affects the supply of loose solid materials along the debris flow in the target detection area. The greater the reserves of loose materials along the gully, the better the conditions for loose solid material supply in the target detection area, resulting in a larger scale of debris flow and a greater risk of landslide and debris flow disasters. The sediment supply section length ratio refers to the cumulative length of sediment supply sections such as collapse, landslide, gully erosion, etc. on both sides and at the bottom of the ditch along the length of the main ditch in the target detection area, reflecting the sediment supply situation of the upstream basin to the downstream basin in the target detection area.

[0062] The hydrodynamic index includes: maximum rainfall in 24 hours. The greater the maximum rainfall in 24 hours, the greater the susceptibility of landslide and mud-rock flow disasters in the target detection area.

[0063] Of course, in other embodiments, the terrain index and provenance index may be adaptively adjusted.

[0064] See also Figure 3 , Figure 3 This is a flow chart of a method for calculating terrain indicators in a landslide and debris flow hazard chain detection method of this application. For step S3: based on the DEM data corresponding to each watershed unit, calculate the terrain indicators corresponding to the watershed unit and assign grades to the terrain indicators.

[0065] The step of calculating the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit further includes the following steps:

[0066] S311: performing geometric calculation on the watershed unit based on the DEM data to obtain the watershed area of ​​the watershed unit;

[0067] S312: Based on the DEM data, perform flow direction analysis on the watershed unit, generate a flow direction grid, and calculate the cumulative flow of the flow direction grid;

[0068] S313: extracting river vector data according to the confluence cumulative flow;

[0069] S314: Divide the river into grades according to the river vector data, perform confluence analysis to obtain a final grade of river, and use the length of the final grade of river as the length of the main ditch;

[0070] S315: taking the ratio of the main ditch length to the basin area as the basin cutting density;

[0071] S316: Calculate the straight-line distance from the starting point to the end point of the final stream, and use it as the straight-line length of the main channel, and use the ratio of the main channel length to the straight-line length of the main channel as the channel curvature;

[0072] S317: Perform regional statistics on the watershed unit according to the DEM data to obtain the maximum elevation and the minimum elevation of the watershed unit, and use the absolute value of the difference between the maximum elevation and the minimum elevation as the relative elevation difference of the watershed.

[0073] In step S311, the DEM data is loaded using ArcGIS software, and the area tool of ArcGIS software, such as the measurement geometry tool, is used to calculate the watershed area for the watershed unit.

[0074] In step S312, the DEM data is loaded and flow direction analysis is performed on the watershed units using the flow direction tool in ArcGIS software. A flow direction grid is generated, and water flow direction data for each flow direction grid is calculated. The flow accumulation tool in ArcGIS software is used to calculate the cumulative flow of each grid unit.

[0075] For step S313, based on the cumulative flow of the confluence, the raster calculator of the ArcGIS software is used to convert the cumulative flow of the confluence of the grid unit into binary data, for example, 1 for rivers and 0 for non-rivers; and then the raster to surface tool of the ArcGIS software is used to convert the binary data into the river vector data.

[0076] For step S314, based on the river vector data, the field calculator tool of ArcGIS software is used to divide the river levels, and then the hydrological analysis tool of ArcGIS software is used to perform confluence analysis to extract the final-level river. Among them, the divided river levels can be divided into first-level rivers, second-level rivers, third-level rivers, fourth-level rivers and fifth-level rivers in turn, the first-level river has the largest confluence cumulative flow, and the fifth-level river has the smallest confluence cumulative flow. The final-level river can be the highest-level river, that is, the first-level river, and the length of the final river is calculated using the measurement tool of ArcGIS software as the length of the main ditch. Of course, in other embodiments, the final-level river can also be the river that finally flows into the main outlet, which is the confluence path and main channel of the water flow in the basin unit.

[0077] For step S316, the starting point and the end point of the final-level river are identified based on the river vector data, and the straight-line distance between the starting point and the end point is measured using the measurement tool or the nearest neighbor analysis tool of the ArcGIS software to obtain the straight-line length of the main ditch.

[0078] For step S317, based on the DEM data, the regional statistical tool of ArcGIS software is used to obtain the maximum elevation and the minimum elevation of the watershed unit, and the absolute value of the difference between the maximum elevation and the minimum elevation is used as the relative elevation difference of the watershed unit.

[0079] See also Figure 4 , Figure 4 This is a flow chart of a method for calculating material source indicators for a landslide and debris flow hazard chain detection method in this application. The method of obtaining landslide hazard susceptibility zoning data, historical borehole catalog data, and current borehole catalog data for the target detection area and calculating the material source indicators corresponding to the watershed units also includes the following steps:

[0080] S321: performing spatial analysis based on the landslide susceptibility zoning data to extract watershed units that are high-susceptibility areas and medium-susceptibility areas for landslide disasters;

[0081] S322: extracting the thickness of the residual slope accumulation layer of the watershed units that are in the high-prone area for landslide disasters and the medium-prone area for landslide disasters respectively, including: using the historical borehole cataloging data as a training data set, the borehole slope, slope aspect, and elevation values ​​in the training data set as feature values, and the historical residual slope accumulation layer thickness as a target variable, training a regression model to obtain a residual slope accumulation layer thickness acquisition model; based on the current borehole cataloging data, using the residual slope accumulation layer thickness acquisition model to obtain residual slope accumulation layer thickness distribution data of the target detection area; extracting the residual slope accumulation layer thickness of the watershed units that are in the high-prone area for landslide disasters and the medium-prone area for landslide disasters according to the residual slope accumulation layer thickness distribution data;

[0082] S323: Calculating the average thickness of the residual slope deposits of the watershed units that are the high-prone landslide disaster area and the medium-prone landslide disaster area to obtain the average thickness of the loose materials in the sand-producing area;

[0083] S324: performing geometric calculations on the watershed units that are the high-prone landslide disaster area and the medium-prone landslide disaster area to obtain the areas of the high-prone landslide disaster area and the medium-prone landslide disaster area, multiplying the areas of the high-prone landslide disaster area and the medium-prone landslide disaster area by the area of ​​the high-prone landslide disaster area, and then adding the multiplications to obtain the reserves of loose materials along the ditch;

[0084] S325: extracting, based on the river vector data, river basin units having the river whose confluence cumulative flow is greater than a predetermined threshold as sediment supply basin units, and calculating the sediment supply length of the sediment supply basin units based on the DEM data;

[0085] S326: Obtain the sediment supply section length of the sediment supply watershed unit at the previous level, and add the sediment supply section length to the sediment supply length to obtain the sediment supply section length of the sediment supply watershed unit;

[0086] S327: Calculate the ratio of the length of the sediment supply section to the length of the main ditch as the sediment supply section length ratio.

[0087] For steps S321 and S322, landslide susceptibility zoning data for the target detection area can be obtained from a geological environment monitoring agency. The landslide susceptibility zoning data is typically in the form of raster data or vector data. The landslide susceptibility zoning data can be loaded using ArcGIS software, and a new landslide susceptibility zoning layer can be generated using ArcGIS software's spatial analysis functions, such as "Extract by Attributes."

[0088] The overlay analysis tool of ArcGIS software is used to overlay the watershed units of the landslide susceptibility zoning layer to screen out watershed units containing high-susceptibility areas and medium-susceptibility areas.

[0089] Of course, the landslide hazard susceptibility zoning data of the target detection area can also be obtained from the geological data sharing website of the Institute of Geological Sciences or other geological data public databases.

[0090] In this embodiment, the regression model can be a linear regression model. The historical borehole catalog data and the current borehole catalog data can be obtained from a geological database. The historical borehole catalog data and the current borehole catalog data are both data of field drilling and excavation points. Among them, the historical borehole catalog data include: borehole slope, slope aspect, elevation value and the corresponding historical residual slope accumulation layer thickness, and the current borehole catalog data include: borehole slope, slope aspect and elevation value. Using the spatial analysis function in ArcGIS software, the residual slope accumulation layer thickness distribution data of the target detection area is superimposed with the watershed units of the high-prone areas and medium-prone areas of landslide disasters to obtain the residual slope accumulation layer thickness of each watershed unit of the high-prone areas and medium-prone areas of landslide disasters, and the average value is calculated to obtain the average thickness of loose materials in the sand-producing area. Among them, the high-prone areas and medium-prone areas of landslide disasters are both regarded as the sand-producing areas.

[0091] In step S324, using the area tool of ArcGIS software, such as the measurement geometry tool, geometric calculations are performed on the watershed units of the high-prone landslide disaster area and the medium-prone landslide disaster area to obtain the area of ​​the high-prone landslide disaster area and the medium-prone landslide disaster area.

[0092] In step S325, based on the river vector data, using the watershed analysis tool in ArcGIS software, watershed units with river segments whose cumulative flow rate exceeds a predetermined threshold are selected as sediment recharge watershed units, where the predetermined threshold may be 3500. The recharge length of the sediment recharge watershed unit refers to the cumulative length of the sediment recharge segments (such as collapse, landslide, gully erosion, etc.) along the banks and bottom of the main ditch. Based on the DEM data, the recharge length of the sediment recharge watershed unit can be obtained using the measurement tool in ArcGIS software.

[0093] Of course, in other embodiments, other geographic information system software (Geographic Information System, GIS for short) may also be used to perform calculations.

[0094] For step S326, it also includes: according to the relative elevation difference of the sediment supply basin unit, obtaining the sediment supply basin unit with the largest relative elevation difference in the basin, and based on the DEM data corresponding to the sediment supply basin unit with the largest relative elevation difference in the basin, obtaining its sediment supply length and using it as its sediment supply section length.

[0095] According to the length of the sediment supply section of the sediment supply watershed unit with the largest relative elevation difference in the watershed, the length of the sediment supply section of each sediment supply watershed unit is obtained by the following method:

[0096]

[0097] in, is the length of the sediment supply section of the current sediment supply basin unit, is the length of the sediment supply section of the upper sediment supply basin unit, and the relative elevation difference of the current sediment supply basin unit is less than the relative elevation difference of the upper sediment supply basin unit, is the sediment supply length of the current sediment supply basin unit, is the length of the sediment supply section of the sediment supply basin unit with the largest relative elevation difference in the basin, The sediment supply length of the sediment supply basin unit with the largest relative elevation difference in the basin.

[0098] See also Figure 5 , Figure 5 This is a flow chart of a method for grading and assigning values ​​to terrain indicators and material source indicators in a landslide and debris flow hazard chain detection method of this application. The grading and assigning values ​​to the terrain indicators and the grading and assigning values ​​to the material source indicators also include the following steps:

[0099] S331: Based on the watershed area, main channel length, watershed relative elevation difference, channel tortuosity, watershed incision density, average thickness of loose materials in the sediment-producing area, loose material reserves along the channel, and length ratio of sediment supply section, the watershed area, main channel length, watershed relative elevation difference, channel tortuosity, watershed incision density, average thickness of loose materials in the sediment-producing area, loose material reserves along the channel, and length ratio of sediment supply section are divided into at least four levels using the natural breakpoint method;

[0100] S332: According to the at least four levels divided by the basin area, main ditch length, basin relative elevation difference, channel curvature, basin cutting density, average thickness of loose matter in the sand-producing area, loose matter reserves along the ditch and sediment supply section length ratio, the basin area, main ditch length, basin relative elevation difference, channel curvature, basin cutting density, average thickness of loose matter in the sand-producing area, loose matter reserves along the ditch and sediment supply section length ratio are assigned corresponding to at least four levels respectively.

[0101] In this embodiment, the basin area (unit: km 2 ) is divided into the following four levels: less than 1, greater than 1 and less than 3, greater than 3 and less than 6, and greater than 6, and the corresponding values ​​are: 5, 4, 3 and 1 respectively. The main ditch length (unit: km) is divided into the following four levels: less than 1, greater than 1 and less than 2.5, greater than 2.5 and less than 4, and greater than 4, and the corresponding values ​​are: 1, 2, 3 and 4 respectively. The relative elevation difference of the watershed (unit: m) is divided into the following four levels: less than 200, greater than 200 and less than 500, greater than 500 and less than 800, and greater than 800, and the corresponding values ​​are: 1, 2, 3 and 4 respectively. The channel curvature is divided into the following four levels: less than 1.2, greater than 1.2 and less than 1.4, greater than 1.4 and less than 1.8, and greater than 1.8, and the corresponding values ​​are: 4, 3, 2 and 1 respectively. The watershed cutting density (unit: km -1 ) is divided into the following four levels: less than 1.6, greater than 1.6 and less than 1.8, greater than 1.8 and less than 2.2, and greater than 2.2, and the corresponding values ​​are: 1, 2, 3 and 4 respectively.

[0102] The average thickness of loose materials in the sand-producing area (unit: m) is divided into the following four levels: less than 8, greater than 8 and less than 9, greater than 9 and less than 10, and greater than 10, and the corresponding values ​​are: 1, 4, 6 and 8. The reserves of loose materials along the ditch (unit: 10 5 m 3 / km 2 ) is divided into the following four levels: less than 5, greater than 5 and less than 10, greater than 10 and less than 30, and greater than 30, and the corresponding values ​​are: 1, 7, 11, and 14. The sediment recharge section length ratio is divided into the following four levels: less than 0.3, greater than 0.3 and less than 0.45, greater than 0.45 and less than 0.6, and greater than 0.6, and the corresponding values ​​are: 1, 8, 12, and 16.

[0103] Of course, in other embodiments, adaptive modifications can be made to the magnitude division and corresponding assignment of the basin area, main ditch length, basin relative elevation difference, channel curvature, basin cutting density, average thickness of loose matter in the sand-producing area, loose material reserves along the ditch and sediment supply section length.

[0104] Regarding step S4: according to the terrain index and the material source index, a comprehensive index method is used to calculate the susceptibility index of landslide and debris flow disasters in the watershed unit.

[0105] The susceptibility index is obtained by substituting the basin area, main channel length, basin relative elevation difference, channel tortuosity, basin incision density, average thickness of loose materials in the sediment-producing area, loose material reserves along the channel, and sediment supply section length ratio into the following formula:

[0106]

[0107] in, is the susceptibility index of the i-th watershed unit, is the jth indicator variable for the i-th watershed unit, 1≤i≤n, 1≤j≤m, n is the number of watershed units, and m is the number of indicator variables, which can be 8. The indicator variables include: watershed area, main channel length, watershed relative elevation difference, channel tortuosity, watershed incision density, average thickness of loose material in the sediment-producing area, loose material reserves along the channel, and sediment supply section length ratio. Of course, in other embodiments, the number of indicator variables can also be adaptively adjusted.

[0108] See also Figure 6 , Figure 6 This is a flow chart of a method for evaluating the accuracy of the susceptibility index of a landslide and debris flow hazard chain detection method in this application. In this embodiment, the accuracy of the susceptibility index is also evaluated, and the specific steps include:

[0109] S41: Dividing the susceptibility index into at least four levels using a natural breakpoint method according to the susceptibility index;

[0110] S42: Based on the at least four levels of the susceptibility index, each of the watershed units is divided into at least four levels of susceptibility, wherein the susceptibility zones include: a high susceptibility area, a medium susceptibility area, a low susceptibility area, and a non-susceptibility area;

[0111] S43: creating a susceptibility assessment zoning map based on the susceptibility zoning, and dividing the susceptibility assessment zoning map into a plurality of statistical units, wherein the number of the statistical units is the same as the number of the watershed units, and any statistical unit corresponds to one susceptibility zoning;

[0112] S44: Acquire historical debris flow disaster data of the target detection area, import it as a surface layer, and overlay it with the susceptibility assessment zoning map for display;

[0113] S45: Counting the area ratios of the statistical units corresponding to the high-probability area, the medium-probability area, and the low-probability area that have experienced historical debris flow disasters, and adding them up in sequence to obtain a first susceptibility ratio; counting the area ratios of the statistical units corresponding to the high-probability area and the medium-probability area that have experienced historical debris flow disasters, and adding them up in sequence to obtain a second susceptibility ratio;

[0114] S46: If the first susceptibility ratio is greater than or equal to 90%, and the second susceptibility ratio is greater than or equal to 60%, the accuracy of the susceptibility index is high; if the first susceptibility ratio is less than 90%, and the second susceptibility ratio is less than 60%, the accuracy of the susceptibility index is low.

[0115] In step S41 and step S42, the susceptibility index is divided into the following four levels: greater than 8 and less than 20, greater than 20 and less than 40, greater than 40 and less than 50, and greater than 50 and less than 59, and the corresponding zones are: non-prone, moderately prone, highly prone, and extremely prone. Of course, in other embodiments, the level division of the susceptibility index and the corresponding zones can be adaptively modified.

[0116] For steps S43 and S44, in this embodiment, the base map is preferably produced by ArcGIS software, and the data of the susceptibility zones are added to the map as layers, and the high-susceptibility areas, medium-susceptibility areas, low-susceptibility areas and non-susceptibility areas are represented by different colors respectively.

[0117] The historical debris flow disaster data refers to regional statistical data on historical debris flow disasters in the target detection area, which can be downloaded from platforms such as the geospatial data cloud. The historical debris flow disaster data can be imported as a surface layer through ArcGIS software and superimposed with the susceptibility assessment zoning map to intuitively display whether historical debris flow disasters have occurred in each statistical unit.

[0118] Regarding step S45, in this embodiment, the accuracy of the susceptibility index is evaluated by superimposing the historical debris flow disaster data on the susceptibility assessment partition map and counting the proportion of historical debris flow disasters occurring in each statistical unit.

[0119] The first susceptibility ratio refers to the sum of the area ratios of the high-susceptibility region, the medium-susceptibility region, and the low-susceptibility region that have experienced historical debris flow disasters. The second susceptibility ratio refers to the sum of the area ratios of the high-susceptibility region and the medium-susceptibility region that have experienced historical debris flow disasters.

[0120] According to the historical debris flow disaster data, debris flow areas with a proportion of more than 90% of the area should be located in the designated high-susceptibility areas, medium-susceptibility areas, and low-susceptibility areas, and debris flow areas with a proportion of more than 60% of the area should be located in the designated high-susceptibility areas and medium-susceptibility areas. Therefore, by determining whether the first susceptibility ratio is greater than or equal to 90% and whether the second susceptibility ratio is greater than or equal to 60%, if they are, the accuracy of the susceptibility index is considered high; if not, the accuracy of the susceptibility index is considered low.

[0121] Regarding step S5: obtaining the rainfall station data of the target detection area, calculating the hydrodynamic index corresponding to the watershed unit, and assigning grades to the hydrodynamic index.

[0122] Among them, see Figure 7 , Figure 7 This is a flow chart of a method for assigning hydrodynamic index classification values ​​to a landslide and debris flow hazard chain detection method of this application, which also includes the following steps:

[0123] S51: Performing Kriging spatial interpolation on the rainfall station data to generate a rainfall raster dataset;

[0124] S52: extracting the 24-hour maximum rainfall in the target detection area according to the rainfall raster dataset;

[0125] S53: Dividing the maximum rainfall in 24 hours into at least four rainfall levels using a natural breakpoint method according to the maximum rainfall in 24 hours;

[0126] S54: assigning values ​​corresponding to at least four rainfall levels to the 24-hour maximum rainfall according to the at least four levels into which the 24-hour maximum rainfall is divided;

[0127] S55: Calculate the area of ​​each rainfall level in the watershed unit according to the rainfall raster dataset, and assign the value of the rainfall level corresponding to the area with the largest area as the 24-hour maximum rainfall of the watershed unit.

[0128] In this embodiment, the rainfall station data can be obtained from a public database of a meteorological department or a hydrological department.

[0129] In step S51, kriging spatial interpolation is performed on the rainfall station data using ArcGIS software. The rainfall station data is added to the ArcGIS software and the coordinate system is set. The geostatistical analysis toolbox of the ArcGIS software is opened, and kriging is selected as the interpolation method for spatial interpolation. After the interpolation is completed, the ArcGIS software generates the rainfall raster dataset, wherein the rainfall raster dataset includes the rainfall values ​​of each watershed unit in the target detection area.

[0130] In step S52, the rainfall raster dataset is loaded using ArcGIS software, a field of rainfall value in the rainfall raster dataset is selected, and the statistical tool of ArcGIS software is used to obtain the maximum value of the field, which is the maximum rainfall in 24 hours.

[0131] In steps S53 and S4, in this embodiment, the 24-hour maximum rainfall (unit: mm) is divided into the following four levels: less than 100, greater than 100 and less than 150, greater than 150 and less than 200, and greater than 200, and the corresponding values ​​are 1, 5, 10, and 16, respectively. Of course, in other embodiments, the level division and corresponding value assignment of the 24-hour maximum rainfall can be adaptively modified.

[0132] In step S55, different areas in the watershed unit correspond to different rainfall levels. Area tools of ArcGIS software, such as measurement geometry tools, are used to calculate the areas of the areas corresponding to different rainfall levels in the watershed unit.

[0133] Regarding step S6: calculating the risk index of landslide and debris flow disasters of the watershed unit according to the susceptibility index and the hydrodynamic index.

[0134] The following steps are also included:

[0135] Substituting the 24-hour maximum rainfall value and the susceptibility index into the following formula, the hazard index is obtained:

[0136]

[0137] in, is the hazard index of the i-th watershed unit, Assign a value to the maximum rainfall in 24 hours for the i-th watershed unit, is the susceptibility index of the i-th watershed unit, 1≤i≤n, 1≤j≤n, where n is the number of watershed units.

[0138] In one embodiment, based on the hazard index, the hazard index is divided into at least four levels using the natural breakpoint method; based on the at least four levels of the hazard index, each of the watershed units is subjected to corresponding at least four levels of hazard zoning, wherein the hazard zoning includes: extremely high hazard area, high hazard area, medium hazard area, and low hazard area. The hazard index is divided into the following four levels: greater than 9 and less than 25, greater than 25 and less than 45, greater than 45 and less than 60, and greater than 60 and less than 75, and the corresponding zonings are: extremely high hazard area, high hazard area, medium hazard area, and low hazard area. Of course, in other embodiments, the hazard index level division and corresponding zoning can be adaptively modified.

[0139] This application fully considers the fragility of the granite weathering crust rock mass in the hilly and mountainous areas of South China, resulting in a loose weathering layer on the upper part of the mountain and a hard, slightly weathered bedrock on the lower part. This binary structure is extremely prone to landslides under the action of gravity. Therefore, the relative elevation difference of the watershed is specifically selected to represent the height difference between the highest and lowest points within the watershed unit in the hilly and mountainous areas of South China, so as to judge the susceptibility of landslide and mudslide disasters.

[0140] Because South China's hilly and mountainous regions are characterized by high temperatures and high rainfall, with simultaneous warm and cool periods, seasonal droughts and heavy rainfall alternating between them, and continuous rainfall can also cause surface runoff. The mixed movement of surface runoff and loose surface deposits gradually evolves into debris flows. Therefore, topographic indicators such as drainage area, main channel length, channel curvature, and drainage incision density are used to determine the susceptibility to landslides and debris flows. Furthermore, the maximum 24-hour rainfall is used to determine the risk of landslides and debris flows.

[0141] In addition, since soil types such as red soil and red soil are widely distributed in South China, these soils have high clay content and poor permeability, and are easily formed into sand-producing areas under the action of rainfall, providing material sources for landslides and debris flows. Therefore, this application also selects the average thickness of loose materials in sand-producing areas, the reserves of loose materials along the ditch, and the length ratio of sediment supply sections as material source indicators. At the same time, the accumulation bodies produced by landslides and debris flows in the upper-level watershed units, such as soil clay, are included in the landslide and debris flow material sources of the lower-level watershed units, fully considering the along-the-way amplification effect and cumulative amplification effect of the landslide and debris flow disaster chain.

[0142] Example 2

[0143] See also Figure 8 , Figure 8 This is a schematic diagram of a landslide and debris flow disaster chain hazard detection system of the present application. The present application also provides a landslide and debris flow disaster chain hazard detection system, including:

[0144] Watershed unit segmentation module: used to obtain DEM data of the target detection area and divide the target detection area into several watershed units;

[0145] Landslide and debris flow disaster chain indicator system construction module: used to construct a landslide and debris flow disaster chain indicator system, wherein the landslide and debris flow disaster chain indicator system includes terrain indicators, material source indicators and hydrodynamic indicators;

[0146] A terrain index calculation module is used to calculate the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit, and to grade and assign values ​​to the terrain index;

[0147] Material source index calculation module: obtains the landslide hazard susceptibility zoning data, historical borehole catalog data and current borehole catalog data of the target detection area, calculates the material source index corresponding to the watershed unit, and assigns graded values ​​to the material source index;

[0148] Susceptibility index calculation module: used for calculating the susceptibility index of landslide and debris flow disasters of the watershed unit by using a comprehensive index method according to the terrain index and the material source index;

[0149] A hydrodynamic index calculation module is used to obtain rainfall station data in the target detection area, calculate the hydrodynamic index corresponding to the watershed unit, and assign grades to the hydrodynamic index;

[0150] Hazard index calculation module: used to calculate the hazard index of landslide and debris flow disasters in the basin unit based on the susceptibility index and the hydrodynamic index.

[0151] It should be noted that the data obtained by the landslide and debris flow disaster chain hazard detection system provided in this application when implementing a landslide and debris flow disaster chain hazard detection method are stored one-to-one in the storage of this system. When relevant calculations are required, the data required for the calculation can be directly obtained from the storage.

[0152] It should also be noted that the landslide and debris flow hazard chain hazard detection system provided in the above embodiment only uses the division of the above functional modules as an example when implementing a landslide and debris flow hazard chain hazard detection method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the landslide and debris flow hazard chain hazard detection system provided in the above embodiment and the landslide and debris flow hazard chain hazard detection method of Example 1 are of the same concept. The implementation process is detailed in the method embodiment and will not be repeated here.

[0153] The present application is not limited to the above-mentioned embodiments. If various changes or modifications to the present application do not depart from the spirit and scope of the present application, and if these changes and modifications fall within the claims of the present application and the scope of equivalent technologies, the present application is also intended to include these changes and modifications.

Claims

1. A method for detecting the danger of landslide and debris flow disaster chains, characterized in that: The following steps are involved: Obtain DEM data of the target detection area and divide the target detection area into several watershed units; Construct a landslide and debris flow disaster chain index system, wherein the landslide and debris flow disaster chain index system includes terrain indicators, material source indicators and hydrodynamic indicators. The terrain indicators include basin area, main ditch length, basin relative elevation difference, channel curvature and basin cutting density; the material source indicators include: average thickness of loose materials in sand-producing areas, loose material reserves along the ditch and length ratio of sediment supply section; the hydrodynamic indicators include: maximum rainfall in 24 hours; According to the DEM data corresponding to each of the watershed units, the terrain index corresponding to the watershed unit is calculated, and the terrain index is graded and assigned, wherein the calculation of the terrain index includes the following steps: based on the DEM data, geometric calculation is performed on the watershed unit to obtain the watershed area of ​​the watershed unit; Based on the DEM data, flow direction analysis is performed on the watershed unit to generate a flow direction grid, and the cumulative flow of the flow direction grid is calculated; Extracting river vector data according to the confluence cumulative flow; According to the river vector data, the river levels are divided, and a final level of rivers is obtained after confluence analysis, and the length of the final level of rivers is used as the length of the main channel; The ratio of the main groove length to the basin area is used as the basin cutting density; Calculate the straight-line distance from the starting point to the end point of the final-stage river and use it as the straight-line length of the main channel, and use the ratio of the main channel length to the straight-line length of the main channel as the channel curvature; According to the DEM data, regional statistics are performed on the watershed unit to obtain the maximum elevation and the minimum elevation of the watershed unit, and the absolute value of the difference between the maximum elevation and the minimum elevation is used as the relative elevation difference of the watershed; Acquire the landslide susceptibility zoning data, historical borehole cataloging data and current borehole cataloging data of the target detection area, calculate the material source index corresponding to the watershed unit, and grade and assign the material source index, wherein the historical borehole cataloging data includes: borehole slope, slope aspect, elevation value and corresponding historical residual slope accumulation layer thickness, and the current borehole cataloging data includes: borehole slope, slope aspect and elevation value; calculate the material source index, including the following steps: based on the landslide susceptibility zoning data, after spatial analysis, extract the watershed units that are high-prone areas and medium-prone areas for landslide disasters; Respectively extracting the thickness of the residual slope accumulation layer of the watershed units in the areas with high landslide hazard incidence and the areas with medium landslide hazard incidence, including: using the historical borehole cataloging data as a training data set, taking the borehole slope, slope direction, and elevation values ​​in the training data set as feature values, and the historical residual slope accumulation layer thickness as a target variable, training a regression model to obtain a residual slope accumulation layer thickness acquisition model; based on the current borehole cataloging data, using the residual slope accumulation layer thickness acquisition model to obtain residual slope accumulation layer thickness distribution data of the target detection area; extracting the residual slope accumulation layer thickness of the watershed units in the areas with high landslide hazard incidence and the areas with medium landslide hazard incidence according to the residual slope accumulation layer thickness distribution data; The thickness of the residual slope accumulation layer of each watershed unit that is the high-prone area for landslide disasters and the medium-prone area for landslide disasters is averaged to obtain the average thickness of the loose materials in the sand-producing area; Performing geometric calculations on the watershed units of the landslide-prone areas and the landslide-prone areas to obtain the areas of the landslide-prone areas and the landslide-prone areas, respectively multiplying the areas of the landslide-prone areas and the landslide-prone areas with the average thickness of loose materials in the sand-producing area, and then adding them to obtain the loose material reserves along the ditch; According to the river vector data, extracting the river basin unit with the confluence cumulative flow greater than a predetermined threshold as the sediment supply basin unit, and calculating the sediment supply length of the sediment supply basin unit based on the DEM data; Obtaining the length of the sediment supply section of the sediment supply watershed unit at the previous level, and adding the length to the sediment supply length to obtain the length of the sediment supply section of the sediment supply watershed unit; Calculating the ratio of the length of the sediment recharge section to the length of the main ditch as the sediment recharge section length ratio; According to the terrain index and the material source index, the susceptibility index of landslide and debris flow disasters in the watershed unit is calculated by using a comprehensive index method, including the following steps: substituting the watershed area, main ditch length, watershed relative elevation difference, channel curvature, watershed cutting density, average thickness of loose materials in the sand-producing area, loose material reserves along the ditch and sediment supply section length ratio into the following formula to obtain the susceptibility index: in, is the susceptibility index of the ith watershed unit, is the jth indicator variable of the i-th watershed unit, 1≤i≤n, 1≤j≤m, n is the number of the watershed units, m is the number of the indicator variables, and the indicator variables include: the watershed area, the length of the main channel, the relative elevation difference of the watershed, the channel curvature, the watershed cutting density, the average thickness of loose materials in the sand-producing area, the loose material reserves along the channel, and the length ratio of the sediment supply section; Acquiring the rainfall station data of the target detection area, calculating the hydrodynamic index corresponding to the watershed unit, and assigning the hydrodynamic index in a graded manner, including the following steps: performing Kriging spatial interpolation on the rainfall station data to generate a rainfall raster dataset; Extracting the maximum rainfall in the target detection area within 24 hours according to the rainfall raster dataset; According to the maximum rainfall in 24 hours, the maximum rainfall in 24 hours is divided into at least four rainfall levels using a natural breakpoint method; According to the at least four magnitudes of the maximum rainfall in 24 hours, assigning values ​​corresponding to at least four rainfall levels to the maximum rainfall in 24 hours; According to the rainfall raster dataset, the areas of the regions corresponding to the rainfall levels in the watershed unit are calculated respectively, and the value of the region with the largest area corresponding to the rainfall level is used as the 24-hour maximum rainfall value of the watershed unit; According to the susceptibility index and the hydrodynamic index, the hazard index of the landslide and debris flow disaster of the watershed unit is calculated, comprising the following steps: substituting the 24-hour maximum rainfall value and the susceptibility index into the following formula to obtain the hazard index: in, is the hazard index of the ith watershed unit, Assign a value to the maximum rainfall in 24 hours for the i-th watershed unit, is the susceptibility index of the i-th watershed unit, 1≤i≤n, 1≤j≤n, where n is the number of watershed units.

2. A method for detecting the danger of landslide and debris flow disaster chain according to claim 1, characterized in that: The step of obtaining the length of the sediment supply section of the sediment supply watershed unit at the previous level and adding the length of the sediment supply section to the sediment supply length to obtain the length of the sediment supply section of the sediment supply watershed unit comprises the following steps: According to the relative elevation difference of the sediment supply watershed unit, the sediment supply watershed unit with the largest relative elevation difference is obtained, and based on the DEM data corresponding to the sediment supply watershed unit with the largest relative elevation difference, its sediment supply length is obtained and used as its sediment supply section length; According to the length of the sediment supply section of the sediment supply watershed unit with the largest relative elevation difference in the watershed, the length of the sediment supply section of each sediment supply watershed unit is obtained by the following method: in, is the length of the sediment supply section of the current sediment supply basin unit, is the length of the sediment supply section of the upper sediment supply basin unit, and the relative elevation difference of the current sediment supply basin unit is less than the relative elevation difference of the upper sediment supply basin unit, is the sediment recharge length of the current sediment recharge basin unit, is the length of the sediment supply section of the sediment supply basin unit with the largest relative elevation difference in the basin, The sediment recharge length of the sediment recharge basin unit with the largest relative elevation difference in the basin.

3. A method for detecting the danger of landslide and debris flow disaster chain according to claim 1, characterized in that: The step of assigning values ​​to the terrain indexes in a graded manner and the step of assigning values ​​to the material source indexes in a graded manner comprises the following steps: According to the basin area, main channel length, basin relative elevation difference, channel tortuosity, basin cutting density, average thickness of loose materials in the sand-producing area, loose material reserves along the channel and the ratio of the length of the sediment supply section, the basin area, main channel length, basin relative elevation difference, channel tortuosity, basin cutting density, average thickness of loose materials in the sand-producing area, loose material reserves along the channel and the ratio of the length of the sediment supply section are divided into at least four orders of magnitude using the natural breakpoint method; According to the at least four magnitudes divided by the basin area, main channel length, relative elevation difference of the basin, channel tortuosity, basin cutting density, average thickness of loose matter in the sand-producing area, loose material reserves along the ditch and length ratio of the sediment supply section, corresponding at least four levels are assigned to the basin area, main channel length, relative elevation difference of the basin, channel tortuosity, basin cutting density, average thickness of loose matter in the sand-producing area, loose material reserves along the ditch and length ratio of the sediment supply section.

4. A method for detecting the danger of landslide and debris flow disaster chain according to claim 1, characterized in that: The method also includes evaluating the accuracy of the susceptibility index, and the specific steps include: According to the susceptibility index, the susceptibility index is divided into at least four levels using a natural breakpoint method; According to the at least four magnitudes of the susceptibility index, each of the watershed units is zoned into at least four levels of susceptibility, wherein the susceptibility zones include: a high susceptibility area, a medium susceptibility area, a low susceptibility area and a non-susceptibility area; According to the susceptibility zones, a susceptibility assessment zone map is prepared, and the susceptibility assessment zone map is divided into a plurality of statistical units, wherein the number of the statistical units is the same as the number of the watershed units, and any of the statistical units corresponds to one susceptibility zone; Acquire historical debris flow disaster data of the target detection area, import it as a surface layer, and overlay and display it with the susceptibility assessment zoning map; The proportion of the area occupied by historical debris flow disasters in the statistical units corresponding to the high-prone area, the medium-prone area and the low-prone area is counted respectively and added up in sequence to obtain the first proneness ratio; the proportion of the area occupied by historical debris flow disasters in the statistical units corresponding to the high-prone area and the medium-prone area is counted respectively and added up in sequence to obtain the second proneness ratio; If the first susceptibility ratio is greater than or equal to 90% and the second susceptibility ratio is greater than or equal to 60%, the accuracy of the susceptibility index is high; if the first susceptibility ratio is less than 90% and the second susceptibility ratio is less than 60%, the accuracy of the susceptibility index is low.

5. A landslide and debris flow disaster chain hazard detection system, characterized in that: include: Watershed unit segmentation module: used to obtain DEM data of the target detection area and divide the target detection area into several watershed units; Landslide and debris flow disaster chain index system construction module: used to construct a landslide and debris flow disaster chain index system, wherein the landslide and debris flow disaster chain index system includes terrain indicators, material source indicators and hydrodynamic indicators. The terrain indicators include basin area, main ditch length, basin relative elevation difference, channel curvature and basin cutting density; the material source indicators include: average thickness of loose materials in sand-producing areas, loose material reserves along the ditch and sediment supply section length ratio; the hydrodynamic indicators include: maximum rainfall in 24 hours; A terrain index calculation module is used to calculate the terrain index corresponding to each watershed unit according to the DEM data corresponding to each watershed unit, and to grade and assign values ​​to the terrain index, wherein the calculation of the terrain index includes the following steps: based on the DEM data, geometrically calculating the watershed unit to obtain the watershed area of ​​the watershed unit; Based on the DEM data, flow direction analysis is performed on the watershed unit to generate a flow direction grid, and the cumulative flow of the flow direction grid is calculated; Extracting river vector data according to the confluence cumulative flow; According to the river vector data, the river levels are divided, and a final level of rivers is obtained after confluence analysis, and the length of the final level of rivers is used as the length of the main channel; The ratio of the main groove length to the basin area is used as the basin cutting density; Calculate the straight-line distance from the starting point to the end point of the final-stage river and use it as the straight-line length of the main channel, and use the ratio of the main channel length to the straight-line length of the main channel as the channel curvature; According to the DEM data, regional statistics are performed on the watershed unit to obtain the maximum elevation and the minimum elevation of the watershed unit, and the absolute value of the difference between the maximum elevation and the minimum elevation is used as the relative elevation difference of the watershed; Material source index calculation module: obtain the landslide susceptibility zoning data, historical borehole cataloging data and current borehole cataloging data of the target detection area, calculate the material source index corresponding to the watershed unit, and grade the material source index, wherein the historical borehole cataloging data includes: borehole slope, slope aspect, elevation value and corresponding historical residual slope accumulation layer thickness, and the current borehole cataloging data includes: borehole slope, slope aspect and elevation value; calculate the material source index, including the following steps: based on the landslide susceptibility zoning data, after spatial analysis, extract the watershed units that are high-prone areas and medium-prone areas for landslide disasters; Respectively extracting the thickness of the residual slope accumulation layer of the watershed units in the areas with high landslide hazard incidence and the areas with medium landslide hazard incidence, including: using the historical borehole cataloging data as a training data set, taking the borehole slope, slope direction, and elevation values ​​in the training data set as feature values, and the historical residual slope accumulation layer thickness as a target variable, training a regression model to obtain a residual slope accumulation layer thickness acquisition model; based on the current borehole cataloging data, using the residual slope accumulation layer thickness acquisition model to obtain residual slope accumulation layer thickness distribution data of the target detection area; extracting the residual slope accumulation layer thickness of the watershed units in the areas with high landslide hazard incidence and the areas with medium landslide hazard incidence according to the residual slope accumulation layer thickness distribution data; The thickness of the residual slope accumulation layer of each watershed unit that is the high-prone area for landslide disasters and the medium-prone area for landslide disasters is averaged to obtain the average thickness of the loose materials in the sand-producing area; Performing geometric calculations on the watershed units of the landslide-prone areas and the landslide-prone areas to obtain the areas of the landslide-prone areas and the landslide-prone areas, respectively multiplying the areas of the landslide-prone areas and the landslide-prone areas with the average thickness of loose materials in the sand-producing area, and then adding them to obtain the loose material reserves along the ditch; According to the river vector data, extracting the river basin unit with the confluence cumulative flow greater than a predetermined threshold as the sediment supply basin unit, and calculating the sediment supply length of the sediment supply basin unit based on the DEM data; Obtaining the length of the sediment supply section of the sediment supply watershed unit at the previous level, and adding the length to the sediment supply length to obtain the length of the sediment supply section of the sediment supply watershed unit; Calculating the ratio of the length of the sediment recharge section to the length of the main ditch as the sediment recharge section length ratio; Susceptibility index calculation module: used to calculate the susceptibility index of landslide and debris flow disasters of the watershed unit by using a comprehensive index method according to the terrain index and the material source index, including the following steps: substituting the watershed area, main ditch length, watershed relative elevation difference, channel curvature, watershed cutting density, average thickness of loose materials in the sand-producing area, loose material reserves along the ditch and sediment supply section length ratio into the following formula to obtain the susceptibility index: in, is the susceptibility index of the ith watershed unit, is the jth indicator variable of the i-th watershed unit, 1≤i≤n, 1≤j≤m, n is the number of the watershed units, m is the number of the indicator variables, and the indicator variables include: the watershed area, the length of the main channel, the relative elevation difference of the watershed, the channel curvature, the watershed cutting density, the average thickness of loose materials in the sand-producing area, the loose material reserves along the channel, and the length ratio of the sediment supply section; The hydrodynamic index calculation module is used to obtain the rainfall station data of the target detection area, calculate the hydrodynamic index corresponding to the watershed unit, and grade the hydrodynamic index, including the following steps: performing Kriging spatial interpolation on the rainfall station data to generate a rainfall raster dataset; Extracting the maximum rainfall in the target detection area within 24 hours according to the rainfall raster dataset; According to the maximum rainfall in 24 hours, the maximum rainfall in 24 hours is divided into at least four rainfall levels using a natural breakpoint method; According to the at least four magnitudes of the maximum rainfall in 24 hours, assigning values ​​corresponding to at least four rainfall levels to the maximum rainfall in 24 hours; According to the rainfall raster dataset, the areas of the regions corresponding to the rainfall levels in the watershed unit are calculated respectively, and the value of the region with the largest area corresponding to the rainfall level is used as the 24-hour maximum rainfall value of the watershed unit; The hazard index calculation module is used to calculate the hazard index of the landslide and debris flow disaster of the watershed unit according to the susceptibility index and the hydrodynamic index, comprising the following steps: substituting the 24-hour maximum rainfall value and the susceptibility index into the following formula to obtain the hazard index: in, is the hazard index of the ith watershed unit, Assign a value to the maximum rainfall in 24 hours for the i-th watershed unit, is the susceptibility index of the i-th watershed unit, 1≤i≤n, 1≤j≤n, where n is the number of watershed units.

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