Geological disaster early warning method and system based on model construction

Abstract

The invention relates to the technical field of geological disaster early warning, and discloses a geological disaster early warning method and system based on model construction, and the method comprises the following steps: S1, dividing a target region into a plurality of monitoring units through a dividing module; s2, collecting geological information data in each monitoring unit; s3, collecting environment information data in each monitoring unit; s4, artificial rainfall is carried out on all the monitoring units in sequence, and rainfall is carried out for a preset duration at preset rainfall intensity; s5, analyzing the geological data acquisition unit and the environment information data of each monitoring unit in the rainfall preset duration through an analysis module to obtain a risk index of each monitoring unit; performing risk rating according to the risk index; and S6, early warning of corresponding levels is carried out on each risk level monitoring unit according to the weather forecast information, a worker can preferentially pay attention to the landslide condition of the high-risk monitoring unit according to a risk rating result, and the life safety of residents is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of geological disaster early warning, and in particular to a geological disaster early warning method and system based on model construction. Background Art

[0002] Geological disasters refer to geological phenomena caused by natural or human factors that cause damage and loss to human life, property and the environment. Among them, landslides are a serious type of geological disaster, which refers to the phenomenon that the soil or rock on the slope is affected by factors such as river scouring and rain soaking, and slides down the slope as a whole or in a dispersed manner under the influence of the earth's gravity.

[0003] Rainfall is one of the important factors that trigger landslides. After rainfall, a large amount of rainwater will seep into the soil and rock layers on the slope, and even accumulate on the impermeable layer at the bottom of the slope, thereby increasing the weight of the sliding body. Therefore, real-time monitoring is usually carried out at locations where landslides occur more frequently, and early warnings are issued immediately once a landslide occurs.

[0004] However, as most cities are currently under construction and the geology has undergone tremendous changes, it is difficult to assess the landslide risk in all areas of the city, and therefore it is difficult to predict the location and location of landslides. After an early warning, it is also impossible to determine the safe area, and therefore it is impossible to develop a safer evacuation plan and to protect the lives of residents. Summary of the invention

[0005] The purpose of the present invention is to provide a geological disaster early warning method and system based on model construction to solve the following technical problems:

[0006] How to conduct geological hazard risk assessment in various urban areas.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A geological disaster early warning method based on model construction includes the following steps:

[0009] S1: Divide the target area into several monitoring units through the division module;

[0010] S2: Collecting geological information data in each monitoring unit by setting up geological data collection units in each monitoring unit;

[0011] S3: Collecting environmental information data in each monitoring unit by setting an environmental data collection unit in each monitoring unit;

[0012] S4: Performing artificial rainfall in each monitoring unit in turn with a preset rainfall intensity and a preset rainfall duration;

[0013] S5: By analyzing the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration, the risk index of each monitoring unit is obtained; and risk rating is performed according to the risk index;

[0014] S6: Obtain weather forecast information through external platforms, issue corresponding level warnings to monitoring units of each risk level based on the weather forecast information, and build a model to set up a safe evacuation plan based on the geographical location and risk index of each monitoring unit.

[0015] As a further solution of the present invention: the geological data acquisition unit includes multiple layers of geological acquisition units; the geological acquisition unit includes multiple displacement meters; the geological information data includes real-time displacement change and underground depth of each layer of geological acquisition unit;

[0016] The environmental information data includes real-time rainfall intensity.

[0017] As a further solution of the present invention: by formula:

[0018]

[0019] Calculate the risk index P of the i-th monitoring unit i ;

[0020] Where M is the total number of layers of geological acquisition units, m∈M; r m is the preset weight coefficient of the geological acquisition unit of the mth layer, And r 1 <… <r m ; N is the total number of displacement meters in each geological acquisition unit, n∈N; X mn (t) is the real-time displacement change curve of the nth displacement meter of the mth layer geological acquisition unit over time; Δt is the preset duration of rainfall; θ 1 is the first weight coefficient; θ 2 is the second weight coefficient; θ 3 is the third weight coefficient; X max It is the maximum value of the accumulated displacement change of N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt.

[0021] As a further solution of the present invention: by formula:

[0022]

[0023] Calculate the environmental correction coefficient of the i-th monitoring unit

[0024] Where f(X) is the judgment function. When X>0, f(X)=X; when X≤0, f(X)=0; Q i(t) is the curve of the real-time rainfall intensity of the ith monitoring unit changing with time; Q 0 (t) is the curve of the change of the preset rainfall intensity over time; C 1 is the first preset constant.

[0025] As a further solution of the present invention: by formula:

[0026]

[0027] Calculate the modified risk index X of the i-th monitoring unit i .

[0028] As a further solution of the present invention: the rating process of each monitoring unit is:

[0029] The modified risk index X of the i-th monitoring unit i With the preset threshold [R 1 , R 2 ];

[0030] When X i ≤R 1 When , the risk rating of the i-th monitoring unit is low risk;

[0031] When R 1 <X i ≤R 2 When , the risk rating of the i-th monitoring unit is medium risk;

[0032] When R 2 <X i When , the risk rating of the i-th monitoring unit is high risk.

[0033] As a further solution of the present invention: the preset weight coefficient r of the geological acquisition unit of the mth layer m for:

[0034]

[0035] Among them, H m is the underground depth of the mth geological acquisition unit.

[0036] A geological disaster early warning system based on model construction, the early warning system comprising:

[0037] Division module, which divides the target area into several monitoring units;

[0038] A plurality of geological data acquisition units are arranged in each monitoring unit and are used to acquire geological information data in each monitoring unit;

[0039] A plurality of environmental data collection units are arranged in each monitoring unit and are used to collect environmental information data in each monitoring unit;

[0040] The analysis module conducts artificial rainfall in each monitoring unit with a preset rainfall intensity and a preset rainfall duration; analyzes the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration to obtain the risk index of each monitoring unit; and performs risk rating based on the risk index.

[0041] Beneficial effects of the present invention:

[0042] The present invention divides the target area into a number of monitoring units through a division module; collects geological information data in each monitoring unit by setting a geological data acquisition unit in each monitoring unit; collects environmental information data in each monitoring unit by setting an environmental data acquisition unit in each monitoring unit; performs artificial rainfall in each monitoring unit in turn, with a preset rainfall intensity and a preset rainfall duration; obtains a risk index of each monitoring unit by analyzing the geological data acquisition unit and environmental information data of each monitoring unit within the preset rainfall duration; performs risk rating according to the risk index; obtains meteorological forecast information through an external platform, issues corresponding level warnings to monitoring units of each risk level according to the meteorological forecast information, and constructs a model to set a safe evacuation plan according to the geographical location and risk index of each monitoring unit; the staff can give priority to the landslide situation of the high-risk monitoring unit according to the result of the risk rating, and timely transfer the personnel of the high-risk monitoring unit to the nearby low-risk monitoring unit according to the constructed model to ensure the life safety of the residents. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 A method flow chart of an embodiment of the present invention;

[0045] Figure 2 A system module framework diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] See also Figure 1 As shown, in one embodiment, a geological disaster early warning method based on model construction is provided, comprising the following steps:

[0048] S1: Divide the target area into several monitoring units through the division module;

[0049] S2: Collecting geological information data in each monitoring unit by setting up geological data collection units in each monitoring unit;

[0050] S3: Collecting environmental information data in each monitoring unit by setting an environmental data collection unit in each monitoring unit;

[0051] S4: Performing artificial rainfall in each monitoring unit in turn with a preset rainfall intensity and a preset rainfall duration;

[0052] S5: Analyze the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration through the analysis module to obtain the risk index of each monitoring unit; and perform risk rating according to the risk index;

[0053] S6: Obtain weather forecast information through external platforms, issue corresponding level warnings to monitoring units of each risk level based on the weather forecast information, and build a model to set up a safe evacuation plan based on the geographical location and risk index of each monitoring unit;

[0054] Through the above technical scheme, this embodiment divides the target area into several monitoring units through the division module; by setting a geological data acquisition unit in each monitoring unit, the geological information data in each monitoring unit is collected; by setting an environmental data acquisition unit in each monitoring unit, the environmental information data in each monitoring unit is collected; by performing artificial rainfall in each monitoring unit in turn, with a preset rainfall intensity and a preset rainfall duration; by analyzing the geological data acquisition unit and environmental information data of each monitoring unit within the preset rainfall duration, the risk index of each monitoring unit is obtained; risk rating is performed according to the risk index; meteorological forecast information is obtained through an external platform, and corresponding levels of warnings are issued to monitoring units of each risk level according to the meteorological forecast information, and a model is constructed according to the geographical location and risk index of each monitoring unit to set a safe evacuation plan; the staff can give priority to the landslide situation of the high-risk monitoring unit according to the results of the risk rating, and transfer the personnel of the high-risk monitoring unit to the nearby low-risk monitoring unit in time according to the constructed model to ensure the life safety of the residents;

[0055] It should be noted that the formulation of corresponding level warnings and safe evacuation plans for monitoring units of each risk level based on meteorological forecast information is an existing technology, which is obtained based on experience and will not be described in detail here.

[0056] As an implementation mode of the present invention, the geological data acquisition unit includes multiple layers of geological acquisition units; the geological acquisition unit includes multiple displacement meters; the geological information data includes real-time displacement variation and underground depth of each layer of geological acquisition unit;

[0057] The environmental information data includes real-time rainfall intensity;

[0058] Through the above technical solution, this embodiment specifically obtains real-time displacement changes through a displacement meter; a rain sensor obtains real-time rainfall intensity; the underground depth of each layer of geological acquisition unit is a preset value, obtained based on experience, and will not be described in detail here.

[0059] As an implementation mode of the present invention, by formula:

[0060]

[0061] Calculate the risk index P of the i-th monitoring unit i ;

[0062] Where M is the total number of layers of geological acquisition units, m∈M; r m is the preset weight coefficient of the geological acquisition unit of the mth layer, And r 1 <… <r m ; N is the total number of displacement meters in each geological acquisition unit, n∈N; X mn (t) is the real-time displacement change curve of the nth displacement meter of the mth layer geological acquisition unit over time; Δt is the preset duration of rainfall; θ 1 is the first weight coefficient; θ 2 is the second weight coefficient; θ 3 is the third weight coefficient; X max is the maximum value of the accumulated displacement change of N displacement meters in the mth layer geological acquisition unit during the preset rainfall duration Δt;

[0063] Through the above technical solution, this embodiment is the cumulative displacement change of the nth displacement meter in the mth layer geological acquisition unit during the preset rainfall duration Δt; is the cumulative value of the cumulative displacement changes of the N displacement meters in the geological acquisition unit at the mth layer during the preset rainfall duration Δt; is the cumulative value of the displacement change of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt; is the cumulative value of the displacement change of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. The larger the value, the greater the geological deformation of the m-th layer geological acquisition unit, the greater the landslide risk, and the risk index P of the i-th monitoring unit. i The larger the value, the maximum value X of the cumulative displacement change of N displacement meters in the m-th layer geological acquisition unit during the rainfall preset duration Δt. max The larger the value, the greater the landslide risk of the m-th layer geological acquisition unit. The risk index P of the i-th monitoring unit is i The bigger; is the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt; the larger the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt, the greater the standard deviation, indicating that the cumulative displacement changes of some displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt are greater than the maximum value X of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. max The greater the difference, the smaller the risk, and the risk index P of the i-th monitoring unit i The smaller the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt, the smaller the standard deviation of the cumulative displacement changes of some displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt and the maximum value X of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. max The smaller the difference, the greater the risk. The risk index P of the i-th monitoring unit i The bigger;

[0064] It should be noted that the preset weight coefficient r of the mth layer geological acquisition unit is m , rainfall preset duration Δt, first weight coefficient θ 1 , the second weight coefficient θ 2 and the third weight coefficient θ 3 is a preset value, obtained based on experience, and will not be described in detail here; r 1 It is the uppermost geological collection unit.

[0065] As an implementation mode of the present invention, by formula:

[0066]

[0067] Calculate the environmental correction coefficient of the i-th monitoring unit

[0068] Where f(X) is the judgment function. When X>0, f(X)=X; when X≤0, f(X)=0; Q i (t) is the curve of the real-time rainfall intensity of the ith monitoring unit changing with time; Q 0 (t) is the curve of the change of the preset rainfall intensity over time; C 1 is the first preset constant;

[0069] By formula:

[0070]

[0071] Calculate the modified risk index X of the i-th monitoring unit i ;

[0072] Through the above technical solution, this embodiment is the first cumulative value of the part of the real-time rainfall intensity of the ith monitoring unit that is greater than the preset rainfall intensity within the preset rainfall duration; is the second cumulative value of the part of the real-time rainfall intensity of the ith monitoring unit that is less than the preset rainfall intensity within the preset rainfall duration; when the first cumulative value and hour, When the first cumulative value and hour, X i <P i And the first cumulative value The larger the environmental correction factor The larger the modified risk index X is, the i The smaller the first cumulative value and hour, X i >P i And the second cumulative value The larger the environmental correction factor The smaller the value, the more corrected the risk index X is. i The bigger;

[0073] It should be noted that the preset rainfall intensity variation curve Q 0 (t) is a preset curve; the first preset constant C 1 These are preset values, which are obtained based on experience and will not be described in detail here.

[0074] As an implementation mode of the present invention, the rating process of each monitoring unit is as follows:

[0075] The modified risk index X of the i-th monitoring unit i With the preset threshold [R 1 , R 2 ];

[0076] When X i ≤R 1 When , the risk rating of the i-th monitoring unit is low risk;

[0077] When R 1 <X i ≤R 2 When , the risk rating of the i-th monitoring unit is medium risk;

[0078] When R 2 <X i When , the risk rating of the i-th monitoring unit is high risk;

[0079] Through the above technical solution, this embodiment converts the modified risk index X of the i-th monitoring unit into i With the preset threshold [R 1 , R 2 ]; when X i ≤R 1 When R 1 <X i ≤R 2 When R 2 <X i When , the risk rating of the i-th monitoring unit is high risk;

[0080] It should be noted that the preset threshold [R 1 , R 2 ] are preset values, which are obtained based on experience and will not be described in detail here.

[0081] As an implementation mode of the present invention, the preset weight coefficient r of the geological acquisition unit of the mth layer m for:

[0082]

[0083] Among them, H m is the underground depth of the mth geological acquisition unit;

[0084] Through the above technical solution, the deeper the underground depth of the m-th layer geological acquisition unit in this embodiment, the greater the preset weight coefficient r of the m-th layer geological acquisition unit. m The bigger.

[0085] See also Figure 2 As shown, a geological disaster early warning system based on model construction, the early warning system includes:

[0086] Division module, which divides the target area into several monitoring units;

[0087] A plurality of geological data acquisition units are arranged in each monitoring unit and are used to acquire geological information data in each monitoring unit;

[0088] A plurality of environmental data collection units are arranged in each monitoring unit and are used to collect environmental information data in each monitoring unit;

[0089] The analysis module conducts artificial rainfall in each monitoring unit with a preset rainfall intensity and a preset rainfall duration; analyzes the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration to obtain the risk index of each monitoring unit; and performs risk rating according to the risk index;

[0090] Through the above technical scheme, this embodiment divides the target area into several monitoring units through the division module; by setting a geological data acquisition unit in each monitoring unit, the geological information data in each monitoring unit is collected; by setting an environmental data acquisition unit in each monitoring unit, the environmental information data in each monitoring unit is collected; by carrying out artificial rainfall in each monitoring unit in turn, with a preset rainfall intensity and a preset rainfall duration; by analyzing the geological data acquisition unit and environmental information data of each monitoring unit within the preset rainfall duration, the risk index of each monitoring unit is obtained; risk rating is performed according to the risk index; the staff can give priority to the landslide situation of the high-risk monitoring unit according to the results of the risk rating, and transfer the personnel of the high-risk monitoring unit to the low-risk monitoring unit in time to ensure the life safety of the residents.

[0091] Working principle of the present invention:

[0092] First, through the formula:

[0093]

[0094] Calculate the preset weight coefficient r of the mth layer geological acquisition unit m

[0095] Among them, H m is the underground depth of the mth geological acquisition unit;

[0096] The deeper the underground depth of the m-th layer geological acquisition unit is, the higher the preset weight coefficient r of the m-th layer geological acquisition unit is. m The bigger

[0097] Then through the formula:

[0098]

[0099] Calculate the risk index P of the i-th monitoring unit i ; is the cumulative displacement change of the nth displacement meter in the mth layer geological acquisition unit during the preset rainfall duration Δt; is the cumulative value of the cumulative displacement changes of the N displacement meters in the geological acquisition unit at the mth layer during the preset rainfall duration Δt; is the cumulative value of the displacement change of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt; is the cumulative value of the displacement change of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. The larger the value, the greater the geological deformation of the m-th layer geological acquisition unit, the greater the landslide risk, and the risk index P of the i-th monitoring unit. i The larger the value, the maximum value X of the cumulative displacement change of N displacement meters in the m-th layer geological acquisition unit during the rainfall preset duration Δt. maxThe larger the value, the greater the landslide risk of the m-th layer geological acquisition unit. The risk index P of the i-th monitoring unit is i The bigger; is the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt; the larger the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt, the greater the standard deviation, indicating that the cumulative displacement changes of some displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt are greater than the maximum value X of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. max The greater the difference, the smaller the risk, and the risk index P of the i-th monitoring unit i The smaller the standard deviation of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt, the smaller the standard deviation of the cumulative displacement changes of some displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt and the maximum value X of the cumulative displacement changes of the N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt. max The smaller the difference, the greater the risk. The risk index P of the i-th monitoring unit i The bigger;

[0100] Then through the formula:

[0101]

[0102] Calculate the environmental correction coefficient of the i-th monitoring unit

[0103] Where f(X) is the judgment function. When X>0, f(X)=X; when X≤0, f(X)=0; Q i (t) is the curve of the real-time rainfall intensity of the ith monitoring unit changing with time; Q 0 (t) is the curve of the change of the preset rainfall intensity over time; C 1 is the first preset constant;

[0104] By formula:

[0105]

[0106] Calculate the modified risk index X of the i-th monitoring unit i ;

[0107] is the first cumulative value of the part of the real-time rainfall intensity of the ith monitoring unit that is greater than the preset rainfall intensity within the preset rainfall duration; is the second cumulative value of the part of the real-time rainfall intensity of the ith monitoring unit that is less than the preset rainfall intensity within the preset rainfall duration; when the first cumulative value and hour, When the first cumulative value and hour, X i <P i And the first cumulative value The larger the environmental correction factor The larger the modified risk index X is, the i The smaller the first cumulative value and hour, X i >P i And the second cumulative value The larger the environmental correction factor The smaller the value, the more corrected the risk index X is. i The larger the value, the higher the risk index X of the i-th monitoring unit. i With the preset threshold [R 1 , R 2 ]; when X i ≤R 1 When R 1 <X i ≤R 2 When R 2 <X i When , the risk rating of the i-th monitoring unit is high risk.

[0108] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A geological disaster early warning method based on model construction, characterized in that: The following steps are involved: S1: Divide the target area into several monitoring units through the division module; S2: Collecting geological information data in each monitoring unit by setting up geological data collection units in each monitoring unit; S3: Collecting environmental information data in each monitoring unit by setting an environmental data collection unit in each monitoring unit; S4: Performing artificial rainfall in each monitoring unit in turn with a preset rainfall intensity and a preset rainfall duration; S5: By analyzing the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration, the risk index of each monitoring unit is obtained; and risk rating is performed according to the risk index; S6: Obtain weather forecast information through external platforms, issue corresponding level warnings to monitoring units of each risk level based on the weather forecast information, and build a model to set up a safe evacuation plan based on the geographical location and risk index of each monitoring unit.

2. A geological disaster early warning method based on model construction according to claim 1, characterized in that: The geological data acquisition unit includes multiple layers of geological acquisition units; the geological acquisition unit includes multiple displacement meters; the geological information data includes real-time displacement change and underground depth of each layer of geological acquisition unit; The environmental information data includes real-time rainfall intensity.

3. A geological disaster early warning method based on model construction according to claim 2, characterized in that: By formula: Calculate the risk index P of the i-th monitoring unit i ; Where M is the total number of layers of geological acquisition units, m∈M; r m is the preset weight coefficient of the geological acquisition unit of the mth layer, And r1<… <r m ; N is the total number of displacement meters in each geological acquisition unit, n∈N; X mn (t) is the real-time displacement change curve of the nth displacement meter of the mth layer geological acquisition unit over time; Δt is the preset duration of rainfall; θ1 is the first weight coefficient; θ2 is the second weight coefficient; θ3 is the third weight coefficient; X max It is the maximum value of the accumulated displacement change of N displacement meters in the m-th layer geological acquisition unit during the preset rainfall duration Δt.

4. A geological disaster early warning method based on model construction according to claim 3, characterized in that: By formula: Calculate the environmental correction coefficient of the i-th monitoring unit Where f(X) is the judgment function. When X>0, f(X)=X; when X≤0, f(X)=0; Q i (t) is the curve of the real-time rainfall intensity of the ith monitoring unit changing with time; Q0(t) is the curve of the preset rainfall intensity changing with time; C1 is the first preset constant.

5. A geological disaster early warning method based on model construction according to claim 4, characterized in that: By formula: Calculate the modified risk index X of the i-th monitoring unit i .

6. A geological disaster early warning method based on model construction according to claim 5, characterized in that: The rating process for each monitoring unit is as follows: The modified risk index X of the i-th monitoring unit i and the preset threshold [R1, R2]; When X i When ≤R1, the risk rating of the i-th monitoring unit is low risk; When R1 <X i When ≤R2, the risk rating of the ith monitoring unit is medium risk; When R2 <X i When , the risk rating of the i-th monitoring unit is high risk.

7. A geological disaster early warning method based on model construction according to claim 6, characterized in that: The preset weight coefficient r of the geological acquisition unit in the mth layer m for: Among them, H m is the underground depth of the mth geological acquisition unit.

8. A geological disaster early warning system based on model construction, applicable to a geological disaster early warning method based on model construction as claimed in any one of claims 1 to 7, characterized in that: The early warning system includes: Division module, which divides the target area into several monitoring units; A plurality of geological data acquisition units are arranged in each monitoring unit and are used to acquire geological information data in each monitoring unit; A plurality of environmental data collection units are arranged in each monitoring unit and are used to collect environmental information data in each monitoring unit; The analysis module conducts artificial rainfall in each monitoring unit with a preset rainfall intensity and a preset rainfall duration; analyzes the geological data collection unit and environmental information data of each monitoring unit within the preset rainfall duration to obtain the risk index of each monitoring unit; and performs risk rating based on the risk index.

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