Geological disaster risk monitoring system

Abstract

The invention discloses a geological disaster risk monitoring system, and relates to the technical field of disaster risk monitoring, and the system comprises a data unit which is used for obtaining historical debris flow disaster data and regional data of a target region; the model danger unit is used for obtaining a first danger index, and the obtaining mode of the first danger index is as follows: the expert danger unit is used for obtaining an area map based on the area data, marking the area map to obtain a dangerous area, and obtaining a second danger index based on the dangerous area; the comprehensive danger unit is used for obtaining a regional danger index based on the first danger index and the second danger index; the monitoring unit is used for obtaining a monitoring result based on the regional danger index; the problems that an existing small watershed debris flow disaster monitoring mode mainly conducts monitoring through expert experience, objectivity is lacked, false alarm and missed alarm are prone to occurring, and the accuracy of disaster early warning is low can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of disaster risk monitoring, and in particular to a geological disaster risk monitoring system. Background Art

[0002] The sudden and rapid surface runoff caused by rainfall in the small watershed of Reshui River is often characterized by rapid rise and fall due to the small watershed area, short valleys, and the fact that surface runoff often converges in relatively narrow streams and rivers, as well as some waterways with periodic use and waste. Therefore, the surface runoff time is short and often shows the characteristics of sudden rise and fall. Strong hydrodynamic conditions can be generated in the valley under short-term high-intensity rainfall, and loose deposits are prone to form debris flows under the action of huge water flow scouring force. Debris flows in small watersheds are characterized by large quantity and wide range. They are mostly closely related to local landslides after the slope is saturated with water. They are characterized by hidden locations and rapid disasters, and it is difficult to successfully avoid risks after they occur.

[0003] At present, the main method of monitoring debris flow disasters in small watersheds is for experts to monitor and warn of debris flow disasters in small watersheds based on precipitation and past experience. However, expert evaluations are subjective and prone to false alarms and missed alarms. The accuracy of disaster warnings needs to be improved. Summary of the invention

[0004] In order to solve the problem that the existing small watershed debris flow disaster monitoring method is mainly based on expert experience, lacks objectivity, is prone to false alarms and missed alarms, and leads to low accuracy of disaster warning, the present invention provides a geological disaster risk monitoring system, the system includes:

[0005] Data unit: used to obtain historical debris flow disaster data and regional data of the target area;

[0006] Model risk unit: used to obtain a first risk index, wherein the first risk index is obtained in the following manner:

[0007] Based on the regional data and the first pre-trained model, the target area is screened to obtain a potential debris flow area; the water flow process of unsaturated soil in the potential debris flow area is simulated to obtain precipitation intensity; the slope single width flow and safety factor of the potential debris flow area are obtained, and the total runoff is obtained based on the precipitation intensity, the slope single width flow and the safety factor, and the bulk density is obtained based on the total runoff, and the first hazard index is obtained based on the bulk density;

[0008] Expert danger unit: used for obtaining a regional map based on the regional data, marking the regional map to obtain a danger zone, and obtaining a second danger index based on the danger zone;

[0009] Comprehensive risk unit: used for obtaining a regional risk index based on the first risk index and the second risk index;

[0010] Monitoring unit: used to obtain monitoring results based on the regional hazard index.

[0011] The present invention follows the principles of regional suitability and availability of basic data, selects a pre-trained model based on the debris flow initiation mechanism, and uses the model to monitor debris flows in small watersheds for greater objectivity. Experts in this field combine the geology, soil, land cover and meteorological weather of the small watersheds, and based on subjective experience, mark possible debris flow occurrence areas. The two methods are combined for monitoring to reduce false alarms and missed alarms and improve the accuracy of disaster warnings.

[0012] The essence of disaster losses is the distorted regional socioeconomic situation, which is highlighted by disaster events. These socioeconomic conditions involve many aspects from individuals to groups, including the limited production and living resources of individuals due to their gender, age, health status, occupation and other factors when facing disasters, as well as the socioeconomic disadvantages of groups such as weak infrastructure, uneven resource distribution, and low education level. After a disaster event occurs, various socioeconomic factors interact with each other and ultimately determine the extent of losses and adverse effects caused by the disaster. For example, areas with weak infrastructure usually lack sufficient emergency response capabilities; areas with uneven resource distribution may result in vulnerable groups being unable to obtain emergency rescue equipment and supplies in a timely manner; individual characteristics lead to high vulnerability of groups, and they often lack the necessary disaster knowledge and coping skills. Through scientific assessment of disaster vulnerability, high-risk areas and groups can be identified, targeted disaster warning and preparedness measures can be designed, the overall disaster resistance of the region can be systematically improved, and social equity and sustainable socioeconomic development can be ensured. Therefore, it is necessary to assess vulnerability.

[0013] Furthermore, the system further comprises:

[0014] Social vulnerability unit: used to obtain the vulnerability level and update the monitoring result based on the vulnerability level;

[0015] The vulnerability level is obtained as follows:

[0016] Based on the historical debris flow disaster data and the regional data, social data is obtained, and the social data is analyzed to obtain change data; the change data is identified and features are extracted to obtain subject and spatiotemporal characteristics; based on the subject and the spatiotemporal characteristics, a vulnerability index is obtained, and based on the vulnerability index and preset weights, a comprehensive index is obtained; based on the comprehensive index, the vulnerability level is obtained.

[0017] For individuals, the essence of vulnerability lies in the limitations of production and living factors such as personal capabilities, resources and infrastructure, so it is necessary to collect relevant risk information for individuals. The individual information collection of this system mainly includes two forms, namely, collecting images of the target area, identifying pedestrian behavior based on the images, extracting information related to debris flow risks, such as distinguishing between farming in the fields and farming in the mountains to determine the number of people stranded due to the disaster, and prompting emergency shelters; and receiving the risk information reported by users, prompting emergency shelters, thereby reducing safety issues caused by debris flow disasters.

[0018] Furthermore, the system further comprises an individual vulnerability unit, and the individual vulnerability unit comprises:

[0019] The first unit is used to determine whether there are stranded people in the target area based on the second pre-trained model and the area data, and if so, obtain a first emergency shelter point based on the area data and the shelter data;

[0020] The second unit is used to obtain the coordinates of the target person, and determine whether the target person is located in a dangerous position based on the coordinates of the target person. If so, a second emergency avoidance point is obtained based on the coordinates of the target person, the area data and the avoidance data.

[0021] Furthermore, the individual vulnerability unit also includes:

[0022] Emergency shelter unit: used to obtain the shelter data, which includes core shelters, temporary shelters and shelter routes;

[0023] The core safe haven is obtained by: obtaining a resistance surface factor based on the regional data, constructing a comprehensive resistance surface based on the resistance surface factor, extracting a pattern of the comprehensive resistance surface based on a third pre-trained model, corroding the pattern to obtain a potential safe haven, obtaining a point density of the potential safe haven, and obtaining a core safe haven based on the point density;

[0024] The temporary shelter is obtained by: obtaining the area of ​​the potential shelter, and obtaining the temporary shelter based on the area and the core shelter;

[0025] The method for obtaining the risk avoidance path is: extracting the bridge area based on the image spots, and obtaining the risk avoidance path based on the bridge area. Further, the first calculation formula for obtaining the potential debris flow area is:

[0026] L = Ln-0.2515*ln-3.485;

[0027] Among them, L represents the judgment parameter for determining whether the target area is a potential debris flow area, Ln represents the basin height, and ln represents the basin area.

[0028] Furthermore, the second calculation formula for obtaining the precipitation intensity is:

[0029]

[0030] Among them, S e represents saturation, α represents atmospheric pressure, ψ represents soil matrix suction, n and m represent curve shape parameters, k(θ,z) represents unsaturated soil permeability, k 0 represents the saturated hydraulic conductivity of the topsoil, θ represents the soil moisture content, z represents the direction, S e represents saturation, m represents the curve shape parameter, exp(-fz) represents the exponential decay factor, represents partial derivative, θ(z,t) represents soil moisture content in the z direction at time t, and q v (θ,z) represents soil water flux, t represents time, R represents precipitation intensity, Γ represents boundary, d represents the normal direction of boundary Γ, θ(0,t) represents the moisture content at the depth z=0 of the topsoil at time t, h 0 Indicates the depth of water accumulation. Further, the third calculation formula for obtaining the single-width flow of the slope is:

[0031]

[0032] Among them, y represents the flow rate per width of the slope, x1 represents the Manning coefficient, x2 represents the slope, and x3 represents the net water depth after deducting the depression;

[0033] The fourth calculation formula for obtaining the safety factor is:

[0034]

[0035] Among them, F S represents the safety factor, β represents the soil slope, represents the internal friction angle of soil, c represents the soil cohesion, represents the nonlinear relationship, ψ represents the soil matrix suction, H s represents the soil layer thickness, γ t Indicates the total unit weight of the soil. Further, the fifth calculation formula for obtaining the total amount of runoff is:

[0036]

[0037]

[0038] Among them, W w represents the total runoff, W s represents the amount of soil instability, N represents the number of grids, A i represents the grid unit area of ​​the i-th grid, Dr Indicates the runoff depth, N ins Indicates the number of grids for soil instability, D ins represents the instability depth, i represents the parameter, and t represents the time.

[0039] Furthermore, the sixth calculation formula for obtaining the bulk density is:

[0040]

[0041] Where ρ represents the bulk density, ρ w Represents the density of water, V w represents the volume of water, ρ s Represents the density of solid particles, V s Indicates the volume of destroyed soil.

[0042] Furthermore, the seventh calculation formula for obtaining the potential safe haven is:

[0043]

[0044] Among them, MCR represents the minimum cumulative resistance model, D i represents the spatial distance from source j to landscape unit i, R i represents the ecological resistance coefficient of landscape unit i, f 1 It indicates the positive correlation between the minimum cumulative resistance and the ecological process, i and j are constants, a and b represent the number of landscape units and source areas, respectively.

[0045] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0046] 1. The present invention follows the principles of regional suitability and availability of basic data, selects a pre-trained model based on the debris flow initiation mechanism, and uses the model to monitor debris flows in small watersheds, which is more objective. Experts in this field combine the geology, soil, land cover and meteorological weather of the small watershed, and mark possible debris flow occurrence areas based on subjective experience. The two methods are combined for monitoring to reduce false alarms and missed alarms and improve the accuracy of disaster warnings.

[0047] 2. Obtaining vulnerability levels, updating monitoring results based on vulnerability levels, and combining monitoring with regional socio-economic conditions can improve the accuracy of debris flow disaster warnings.

[0048] 3. Based on the second pre-trained model and regional data, determine whether there are stranded people in the target area. If so, obtain the first emergency shelter point based on the regional data and the risk avoidance data; obtain the coordinates of the target person, and determine whether the target person is in a dangerous position based on the coordinates of the person. If so, obtain the second emergency shelter point based on the coordinates of the person, regional data and risk avoidance data, and prompt the emergency shelter point to reduce the safety problems caused by mudslide disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation on the embodiments of the present invention;

[0050] Figure 1 It is a flow chart of a geological disaster risk monitoring system in the present invention;

[0051] Figure 2 is a schematic diagram of a process for obtaining a first risk index in the present invention;

[0052] Figure 3 is a schematic diagram of a process for obtaining risk hedging data in the present invention;

[0053] Figure 4 is a schematic diagram of a process for obtaining a vulnerability level in the present invention;

[0054] Figure 5 It is a schematic diagram of the process of obtaining the second pre-training model in the present invention. DETAILED DESCRIPTION

[0055] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those within the scope of this description. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0057] Embodiment 1

[0058] refer to Figure 1-Figure 2 This embodiment provides a geological disaster risk monitoring system, the system comprising:

[0059] Data unit: used to obtain historical debris flow disaster data and regional data of the target area;

[0060] Model risk unit: used to obtain a first risk index, wherein the first risk index is obtained in the following manner:

[0061] Based on the regional data and the first pre-trained model, the target area is screened to obtain a potential debris flow area; the water flow process of unsaturated soil in the potential debris flow area is simulated to obtain precipitation intensity; the slope single width flow and safety factor of the potential debris flow area are obtained, and the total runoff is obtained based on the precipitation intensity, the slope single width flow and the safety factor, and the bulk density is obtained based on the total runoff, and the first hazard index is obtained based on the bulk density;

[0062] In this embodiment, the regional data includes geological data, topographic data, soil data, vegetation cover data and meteorological data;

[0063] The first pre-trained model may be a distributed hydrological model (GBHM, Geomorphology-Based Hydrological Model);

[0064] For example, based on the regional data and the GBHM model, the target area is screened according to the basin height and basin area to obtain the potential debris flow area; the one-dimensional Richard equation is used to calculate the water flow process in the unsaturated land of each grid in the potential debris flow area to obtain the precipitation intensity: the Van Genuchten model is used to describe the relationship between soil matrix suction and land water content, and the unsaturated soil permeability parameters are calculated. The boundary condition for surface soil water production depends on the precipitation intensity. Only when the precipitation intensity is greater than the saturated permeability of the surface soil will surface runoff occur.

[0065] When the surface water exceeds the water storage capacity of the slope depression and generates runoff, the single-width flow rate of the slope in the potential debris flow area can be calculated by the Manning formula. The safety factor of soil instability is calculated based on the Mohr-Coulomb failure criterion of the shallow soil, which is the result of the combined action of soil gravity and shear force. The direction is parallel to the slope, and the safety factor of each grid can be determined based on the limit equilibrium method of infinite slope. The safety factor of each layer of soil in each grid is calculated to determine the runoff depth and instability depth of each grid. Combined with the unit area of ​​the grid, the total runoff and soil instability of several grids at a certain moment can be obtained respectively; the unstable soil and unstable runoff merge to form a water-soil mixture. The bulk density of the water mixture is calculated based on the unstable soil volume and the total volume of surface runoff. The soil volume is obtained based on the unstable soil volume. The volume of the destroyed soil is calculated. The volume of water is obtained based on the total volume of surface runoff. If the bulk density is greater than 1.2, it is determined to be a debris flow and the first hazard index is obtained.

[0066] Expert danger unit: used to obtain a regional map based on the regional data, mark the regional map to obtain the danger zone, and obtain a second danger index based on the danger zone; for example, experts combine regional data with historical debris flow disaster data, based on subjective experience, use the OpenLayers geographic information mapping library to draw points, lines and surfaces on the map, mark possible debris flow occurrence areas, and obtain the second danger index.

[0067] Comprehensive risk unit: used to obtain a regional risk index based on the first risk index and the second risk index; such as assigning different weights to the first risk index and the second risk index, and adding them together to obtain the regional risk index.

[0068] Monitoring unit: used to obtain monitoring results based on the regional hazard index.

[0069] The Van Genuchten model (VG model) is a mathematical model used to describe the soil moisture characteristic curve and is widely used in soil hydraulics research. The model describes the water holding characteristics of the soil through four parameters, which are the scale parameter, shape parameters m and n, and saturated water content.

[0070] Embodiment 2

[0071] refer to Figure 1-Figure 4 Based on the first embodiment, in this embodiment, the system further includes:

[0072] Social vulnerability unit: used to obtain the vulnerability level and update the monitoring result based on the vulnerability level;

[0073] The vulnerability level is obtained as follows:

[0074] Based on the historical debris flow disaster data and the regional data, social data is obtained, and the social data is analyzed to obtain change data; in this embodiment, the social data may include population distribution data, economic development data, fixed asset data, social factor data and ecological resource data; the change data may include population change data, urban construction data, industrial development planning data, infrastructure planning data and land use change data;

[0075] The change data are identified and feature extracted respectively to obtain the subject and spatiotemporal features; based on the subject and the spatiotemporal features, a vulnerability index is obtained, as shown in Table 1; based on the vulnerability index and preset weights, a comprehensive index is obtained, such as based on the measurement method of the vulnerability index (as shown in Table 2) and the preset weights (as shown in Table 3), a comprehensive index is obtained;

[0076] Based on the comprehensive index, the vulnerability level is obtained.

[0077] Table 1

[0078]

[0079]

[0080] Table 2

[0081]

[0082]

[0083] Table 3

[0084]

[0085] On the basis of calculating various indicators of debris flow vulnerability, in order to avoid the correlation between various factors affecting the final evaluation results, principal component analysis (PCA) was used to reduce the dimension and finally calculate the comprehensive index.

[0086] Embodiment 3

[0087] refer to Figure 1-Figure 5 Based on the above embodiment, in this embodiment, the system further includes an individual vulnerability unit, and the individual vulnerability unit includes:

[0088] The first unit is used to determine whether there are stranded people in the target area based on the second pre-trained model and the area data, and if so, obtain a first emergency shelter point based on the area data and the shelter data;

[0089] The second unit is used to obtain the coordinates of the target person. If the target person uploads his or her information through the user terminal, it is determined whether the target person is in a dangerous position based on the coordinates of the person. If so, a second emergency avoidance point is obtained based on the coordinates of the person, the area data and the avoidance data.

[0090] In this embodiment, the regional data also includes relevant images collected by cameras at important forks in the town and main mountain road entrances. The second pre-trained model can be an image recognition model that can be trained to recognize pedestrians, etc.

[0091] Embodiment 4

[0092] refer to Figure 1-Figure 5 Based on the above embodiment, in this embodiment, the individual vulnerability unit further includes:

[0093] Emergency shelter unit: used to obtain the shelter data, which includes core shelters, temporary shelters and shelter routes;

[0094] The core safe haven is obtained in the following ways:

[0095] A resistance surface factor is obtained based on the regional data, a comprehensive resistance surface is constructed based on the resistance surface factor, patches of the comprehensive resistance surface are extracted based on the third pre-trained model, the patches are eroded to obtain potential safe havens, the point density of the potential safe havens is obtained, and the core safe havens are obtained based on the point density; the patches that have been eroded are converted into points, and since areas with high point density represent continuous flat land with low land type and disaster resistance, areas with high point density are extracted as core safe havens.

[0096] The temporary shelter is obtained in the following ways:

[0097] Obtain the area of ​​the potential shelter, and obtain a temporary shelter based on the area and the core shelter; perform area analysis on the patches that have been eroded, refer to relevant design specifications for emergency shelters, and use patches with an area greater than 100 square meters that are not core shelters as temporary shelters.

[0098] The method for obtaining the risk avoidance path is as follows:

[0099] Based on the spots, bridge areas are extracted, and the risk avoidance path is obtained based on the bridge areas. The spots are subjected to opening and closing operations and fine line morphological filtering by morphological spatial pattern analysis (MSPA) to extract bridge areas, which are used as risk avoidance paths between spots.

[0100] In this embodiment, the regional data also includes DEM data, land use data and disaster risk area data; the resistance surface factor includes slope resistance factor, land use type resistance factor and risk avoidance factor, and the third pre-trained model can be a minimum cumulative resistance model (Minimum Cumulative Resistance, MCR).

[0101] In the process of constructing the comprehensive resistance surface, the settings of the slope resistance factor, land use type resistance factor and risk avoidance factor can be as follows: for grids with a slope less than 5°, the slope resistance coefficient is defined as 1, and the coefficients for grids with slopes of 5°~10°, 10°~20°, 20°~30° and above 30° are defined as 10, 50, 100 and 200 respectively; the resistance coefficient for land use types such as construction land and grassland is 1, and the resistance coefficients for cultivated land, shrubs, woodlands, wetlands and water bodies are set to 5, 10, 50, 100 and 200 respectively; the resistance coefficient for debris flow danger areas is set to 1 for non-dangerous areas and 200 for debris flow danger areas.

[0102] DEM data (Digital Elevation Model) is a digital model used to represent the elevation information of the earth's surface.

[0103] The bridging area refers to the connecting area between the patterns or between the patterns and other parts such as the edges, which ensures the continuity and stability of the patterns in different resistance values ​​and spaces.

[0104] Embodiment 5

[0105] refer to Figure 1-Figure 5 Based on the above embodiment, in this embodiment, the first calculation formula for obtaining the potential debris flow area is:

[0106] L = Ln-0.2515*ln-3.485;

[0107] Among them, L represents the judgment parameter for determining whether the target area is a potential debris flow area, Ln represents the basin height, and ln represents the basin area.

[0108] The second calculation formula for obtaining the precipitation intensity is:

[0109]

[0110] Among them, S e represents saturation, α represents atmospheric pressure, which is generally 0, and ψ represents soil matrix suction, ψ=u a -u w , is a function of soil moisture content, u a represents the soil air potential, u w represents soil water potential, n and m represent curve shape parameters, n = 1-1 / m, k(θ,z) represents the permeability coefficient of unsaturated soil, k 0 represents the saturated hydraulic conductivity of the topsoil, which is an empirical constant that depends on the soil texture and structure, θ represents the soil water content, z represents the direction, and S e represents saturation, and θ s represents the saturated water content of soil, θ r represents the residual moisture content of soil, θ Δt represents the soil moisture content at the current moment, m represents the curve shape parameter, and exp(-fz) represents the exponential attenuation factor, that is, as the depth z increases, the water conduction decreases exponentially. represents partial derivative, θ(z,t) represents soil moisture content in the z direction at time t, and q v (θ,z) represents soil water flux, t represents time, R represents precipitation intensity, Γ represents boundary, d represents the normal direction of boundary Γ, θ(0,t) represents the moisture content at the topsoil depth z = 0 at time t, θ(0,t) < θ sat is a constraint condition, that is, θ(0,t) is less than the saturated soil moisture content θ sat ,h 0It indicates the depth of water accumulation, that is, the soil reaches a fully saturated state under a specified soil water level height.

[0111] The third calculation formula for obtaining the single-width flow of the slope is:

[0112]

[0113] Among them, y represents the flow rate per width of the slope, x1 represents the Manning coefficient, x2 represents the slope, and x3 represents the net water depth after deducting the depression;

[0114] The fourth calculation formula for obtaining the safety factor is:

[0115]

[0116] Among them, F S represents the safety factor, β represents the soil slope, represents the internal friction angle of soil, c represents the soil cohesion, represents a nonlinear relationship, that is, a nonlinear relationship between pore water pressure and other soil properties. Related to matrix suction, when matrix suction is weak, it is close to the internal friction angle of soil b takes the value of 1, ψ represents the soil matrix suction, H s represents the soil layer thickness, γ t It indicates the total unit weight of soil, including the unit weight of soil particles and water or air in the pores.

[0117] The fifth calculation formula for obtaining the total runoff volume is:

[0118]

[0119]

[0120] Among them, W w represents the total runoff, W s represents the amount of soil instability, N represents the number of grids, A i represents the grid unit area of ​​the i-th grid, D r Indicates the runoff depth, N ins Indicates the number of unstable soil grids, D ins represents the instability depth, i represents the parameter, and t represents the time.

[0121] The sixth calculation formula for obtaining the bulk density is:

[0122]

[0123] Where ρ represents the bulk density, ρ w represents the density of water (ρ w =1.0 g / cm3), Vw represents the volume of water, ρ s represents the density of solid particles (ρ s =2.7 g / cm3), V s Indicates the volume of destroyed soil.

[0124] The seventh calculation formula for obtaining the potential safe haven is:

[0125]

[0126] Among them, MCR represents the minimum cumulative resistance model, D i represents the spatial distance from source j to landscape unit i, R i represents the ecological resistance coefficient of landscape unit i, f 1 It indicates the positive correlation between the minimum cumulative resistance and the ecological process, i and j are constants, a and b represent the number of landscape units and source areas, respectively.

[0127] Embodiment 6

[0128] refer to Figure 1-Figure 5 Based on the above embodiment, in this embodiment, the system further includes a storage unit:

[0129] Used to store the regional data, the historical debris flow disaster data, the social data, the change data, the vulnerability index, the comprehensive index and the risk avoidance data in a database;

[0130] The system further comprises a display unit:

[0131] Used to display the first emergency shelter point, the second emergency shelter point, the character coordinates, the shelter data, the area map, the dangerous area, the area danger index and the vulnerability level.

[0132] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0133] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A geological disaster risk monitoring system, characterized in that: The system comprises: Data unit: used to obtain historical debris flow disaster data and regional data of the target area; Model risk unit: used to obtain a first risk index, wherein the first risk index is obtained in the following manner: Based on the regional data and the first pre-trained model, the target area is screened to obtain a potential debris flow area; the water flow process of unsaturated soil in the potential debris flow area is simulated to obtain precipitation intensity; the slope single width flow and safety factor of the potential debris flow area are obtained, and the total runoff is obtained based on the precipitation intensity, the slope single width flow and the safety factor, and the bulk density is obtained based on the total runoff, and the first hazard index is obtained based on the bulk density; Expert danger unit: used for obtaining a regional map based on the regional data, marking the regional map to obtain a danger zone, and obtaining a second danger index based on the danger zone; Comprehensive risk unit: used for obtaining a regional risk index based on the first risk index and the second risk index; Monitoring unit: used to obtain monitoring results based on the regional hazard index.

2. A geological disaster risk monitoring system according to claim 1, characterized in that: The system further comprises: Social vulnerability unit: used to obtain a vulnerability level and update the monitoring result based on the vulnerability level; The vulnerability level is obtained as follows: Based on the historical debris flow disaster data and the regional data, social data is obtained, and the social data is analyzed to obtain change data; Identify and extract features of the change data respectively to obtain subject and spatiotemporal features; obtain vulnerability indicators based on the subject and the spatiotemporal features, and obtain a comprehensive index based on the vulnerability indicators and preset weights; Based on the comprehensive index, the vulnerability level is obtained.

3. A geological disaster risk monitoring system according to claim 2, characterized in that: The system further comprises an individual vulnerability unit, wherein the individual vulnerability unit comprises: The first unit is used to determine whether there are stranded people in the target area based on the second pre-trained model and the area data, and if so, obtain a first emergency shelter point based on the area data and the shelter data; The second unit is used to obtain the coordinates of the target person, and determine whether the target person is located in a dangerous position based on the coordinates of the target person. If so, a second emergency avoidance point is obtained based on the coordinates of the target person, the area data and the avoidance data.

4. A geological disaster risk monitoring system according to claim 3, characterized in that: The individual vulnerability unit also includes: Emergency shelter unit: used to obtain the shelter data, which includes core shelters, temporary shelters and shelter routes; The core safe haven is obtained in the following ways: Obtaining a resistance surface factor based on the regional data, constructing a comprehensive resistance surface based on the resistance surface factor, extracting a pattern of the comprehensive resistance surface based on a third pre-trained model, corroding the pattern to obtain a potential safe haven, obtaining a point density of the potential safe haven, and obtaining a core safe haven based on the point density; The temporary shelter is obtained in the following ways: Obtaining the area of ​​the potential safe haven, and obtaining a temporary safe haven based on the area and the core safe haven; The method for obtaining the risk avoidance path is as follows: A bridge area is extracted based on the pattern spots, and a risk avoidance path is obtained based on the bridge area.

5. A geological disaster risk monitoring system according to claim 1, characterized in that: The first calculation formula for obtaining the potential debris flow area is: L = Ln-0.2515*ln-3.485; Among them, L represents the judgment parameter for determining whether the target area is a potential debris flow area, Ln represents the basin height, and ln represents the basin area.

6. A geological disaster risk monitoring system according to claim 5, characterized in that: The second calculation formula for obtaining the precipitation intensity is: Among them, S e represents the saturation, α represents the atmospheric pressure, ψ represents the soil matrix suction, n and m represent the curve shape parameters, k(θ,z) represents the unsaturated soil permeability, k0 represents the saturated hydraulic conductivity of the surface soil, θ represents the soil water content, z represents the direction, S e represents saturation, exp(-fz) represents the exponential decay factor, θ represents the partial derivative, θ(z,t) represents the soil moisture content at time t in the z direction, and q v (θ,z) represents soil water flux, t represents time, R represents precipitation intensity, Γ represents boundary, d represents the normal direction of boundary Γ, θ(0,t) represents the moisture content at the topsoil depth z = 0 at time t, h represents water level, and h0 represents water accumulation depth.

7. A geological disaster risk monitoring system according to claim 6, characterized in that: The third calculation formula for obtaining the single-width flow of the slope is: Among them, y represents the flow rate per width of the slope, x1 represents the Manning coefficient, x2 represents the slope, and x3 represents the net water depth after deducting the depression; The fourth calculation formula for obtaining the safety factor is: Among them, F S represents the safety factor, β represents the soil slope, represents the internal friction angle of soil, c represents the soil cohesion, represents the nonlinear relationship, ψ represents the soil matrix suction, H s represents the soil layer thickness, γ t Indicates the total unit weight of soil.

8. A geological disaster risk monitoring system according to claim 7, characterized in that: The fifth calculation formula for obtaining the total runoff volume is: Among them, W w represents the total runoff, W s represents the amount of soil instability, N represents the number of grids, A i represents the unit area of ​​the grid of the i-th grid, D r Indicates the runoff depth, N ins represents the number of unstable grids, D ins represents the instability depth, i represents the parameter, and t represents the time.

9. A geological disaster risk monitoring system according to claim 8, characterized in that: The sixth calculation formula for obtaining the bulk density is: Where ρ represents the bulk density, ρ w Represents the density of water, V w represents the volume of water, ρ s Represents the density of solid particles, V s Indicates the volume of destroyed soil.

10. A geological disaster risk monitoring system according to claim 4, characterized in that: The seventh calculation formula for obtaining the potential safe haven is: Among them, MCR represents the minimum cumulative resistance model, D i represents the spatial distance from source j to landscape unit i, R i represents the ecological resistance coefficient of landscape unit i, f1 represents the positive correlation between the minimum cumulative resistance and the ecological process, i and j both represent constants, a and b represent the number of landscape units and source areas, respectively.

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