A geological disaster monitoring and early warning system

Abstract

The present application relates to a geological disaster monitoring and early warning system applied to the field of disaster early warning, comprising a monitoring module for collecting rainfall, vegetation development, soil moisture content, ground crack development and human activity data, an analysis and judgment module comprising a preliminary analysis and dynamic correction unit, an early warning module for sending an alarm and an escape path, and a simulation module for predicting a disaster path, wherein the vegetation monitoring not only considers soil fixation, but also introduces root system damage effect; the human activity monitoring distinguishes between aboveground engineering and underground engineering, the dynamic correction unit solves the influence of historical early warning residual risk on current evaluation through time decay and main control factor superposition, the system innovatively integrates the two-way influence of engineering efficiency and natural factors, and introduces building impact resistance evaluation, significantly improves early warning accuracy, and is especially suitable for progressive disaster prediction in engineering activity intensive areas.

Description

Technical Field

[0001] This invention relates to a disaster monitoring and early warning system, and more particularly to a geological disaster monitoring and early warning system applied in the field of disaster early warning. Background Technology

[0002] The significance of geological disaster early warning and monitoring lies primarily in reducing losses and protecting lives. It needs to encompass the role of early warning, such as detecting potential hazards in advance and taking measures to avoid casualties and property damage. Simultaneously, it may also be necessary to mention the protection of the ecological environment and economic development, promoting sustainable development.

[0003] Chinese invention patent CN118114992B discloses a remote sensing satellite geological disaster early warning method. By analyzing various geological features, it improves the accuracy of geological risk prediction. By simulating the interaction between water and soil, it enhances the understanding of soil erosion mechanisms and landslide risks, thereby optimizing the effectiveness of disaster early warning.

[0004] Chinese invention patent CN118298609B discloses a debris flow monitoring and early warning system. It uses a monitoring and acquisition module to comprehensively detect surface precipitation, soil mobility, vegetation cover, surface rock area, and slope within the target area. This data is then used as a data analysis block to comprehensively analyze and detect the degree of debris flow hazard within the target area, achieving a comprehensive consideration.

[0005] Existing geological disaster early warning systems typically assess surface water storage capacity by monitoring vegetation, thereby mitigating debris flows. However, during actual debris flows, some plants, such as deep-rooted plants or bamboo, have extensive root systems that loosen the soil surface. When these plants are swept away by debris, the pull of their roots further loosens the soil, exacerbating the damage. Furthermore, existing systems often overlook human intervention, such as the presence of surfaces like platforms or gullies, which can intercept and weaken debris flows in their early stages. Therefore, improvements to the early warning system are necessary. Summary of the Invention

[0006] The technical problem that this invention aims to solve in view of the above-mentioned prior art is...

[0007] To address the aforementioned problems, this invention provides a geological disaster monitoring and early warning system, comprising a monitoring module, a historical storage module, an analysis and judgment module, an early warning module, and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the degree of early warning and to notify the early warning level through the early warning module. The historical storage module is used to store the monitoring data from the monitoring module, and the simulation module is used to simulate the path and speed of debris flow disasters.

[0008] The monitoring module is used to collect environmental parameters of the area to be monitored and warned, including precipitation monitoring unit, vegetation monitoring unit, soil mobility monitoring unit, ground fissure monitoring unit and human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the area to be monitored.

[0009] The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit. The preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module, and the risk dynamic correction unit performs dynamic correction of the risk of the current warning based on the previous warning.

[0010] The human activity monitoring unit includes above-ground engineering monitoring units and underground engineering monitoring units. The above-ground engineering monitoring units are used to monitor the types and distribution areas of buildings on the surface of the area to be monitored and warned, while the underground engineering monitoring units are used to monitor the types and distribution areas of underground construction projects in the area to be monitored.

[0011] In summary, the overall plan and its effects can be described in one sentence regarding the aforementioned geological disaster monitoring and early warning system.

[0012] As a further improvement to this application, the calculation formula for the preliminary analysis unit is as follows:

[0013] R = R(p)*0.2 + R(w)*0.4 + R(g)*0.15 + R(f)*0.1 + R(h)*0.15, where R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. During the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.1. During the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.25.

[0014] As a further improvement to this application, the formula for calculating R(p) is as follows:

[0015] R(p)=E*(1-a*C*Rd*Rm*T)+b*C*Ra*max(0,τ-T 修) ,

[0016] T 修 =T0*(1-0.2*M),

[0017] E represents the basic risk of debris flow without vegetation cover, a and b are calibration coefficients, C is the vegetation cover rate of the area to be tested, and R... d R represents the root density of the plants in the area to be tested. mdenoted as the average root depth of the area to be tested, T0 as the initial root tensile strength of the area to be tested, Ra as the lateral distribution radius of the roots in the area to be tested, and τ as the debris flow shear stress, where M is the soil saturation.

[0018] As a further improvement to this application, the formula for calculating R(h) is as follows:

[0019] R(h) = 1 - + ,in Let At represent the efficiency coefficient of the above-ground works of type t, and At represent the coverage of the above-ground works of type t. This represents the risk gain factor for the j-th type of underground engineering project. Indicates the disturbance intensity of underground engineering of type j. The aboveground impact factor.

[0020] As a further improvement to this application, the formula for calculating R(w) is as follows:

[0021] R(w) = w1 * R w2 +w3, where w1, w2 and w3 are empirical parameters, and R is the drought index;

[0022] R(g) = σtanϕ + D*(1-S), where σ is the effective normal stress, ϕ is the internal friction angle, D is the soil cohesion, and S is the looseness index.

[0023] R(f) = K*(1+F / Fmax)*∇h, where K is the matrix permeability coefficient (m / s), F is the fracture density in m / m², Fmax is the maximum fracture density threshold, and ∇h is the hydraulic gradient.

[0024] As a further improvement of this application, the early warning module includes an early warning signal sending unit and a guidance and avoidance unit. The early warning signal sending unit is used to send an early warning warning signal when the level of early warning risk exceeds a safety threshold. The guidance and avoidance unit sends an escape and avoidance path at the same time as sending the early warning warning signal, based on the simulated disaster occurrence path and speed.

[0025] As another improvement of this application, the risk dynamic correction unit is used to dynamically correct situations where no disaster occurred after the previous warning signal was issued, and the risk level in the preliminary analysis unit does not exceed the safety threshold during the current warning monitoring, but the previous warning characteristics have not yet returned to zero, and there is a potential superimposed threat. The calculation formula is as follows:

[0026] R t修 =R t α*R t−1 + ;

[0027] Rt This is the risk value obtained from preliminary analysis and calculation at the current moment;

[0028] R t修 This is the revised overall risk value for the current moment;

[0029] α: Time decay coefficient, α=e −λΔt λ is the decay rate, and Δt is the time interval;

[0030] β i The weight of the i-th controlling factor satisfies ∑β i =1);

[0031] f(x i ): The normalized contribution function f(x) of the i-th controlling factor i ) = (x i -L i ) / (U i -L i ), U i and L i These are the lower and upper limits of the threshold, respectively.

[0032] As a further improvement to this application, the monitoring module also includes a human activity correction unit, the operation of which is as follows:

[0033] S1, the distance L between the above-ground buildings along the disaster path and the disaster occurrence point;

[0034] S2. Calculate whether the energy carried by the debris flow will damage the buildings when the disaster reaches the coordinates of the buildings on the ground;

[0035] S3. If no damage is caused. If positive, otherwise Multiply by (-1).

[0036] As a further improvement to this application, the impact resistance of the above-ground structure in S2 is N=ζ*(fc*Aw / Ek)*e -k*L Where ζ is the structural type correction factor, fc is the compressive strength of the main building structure, Aw is obtained through BIM database or material testing, Aw is the effective shear area of ​​the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance of the building from the debris flow initiation point, and k is the terrain attenuation factor.

[0037] In summary, the system comprises a monitoring module that collects data on precipitation, vegetation development, soil moisture content, ground fissure development, and human activities; an early warning module for sending alerts and providing escape routes; and a simulation module for predicting disaster paths. Vegetation monitoring considers not only soil stabilization but also root damage effects. Human activity monitoring is divided into above-ground and underground engineering activities. The dynamic correction unit addresses the impact of residual risks from historical warnings on current assessments through time decay and the superposition of key control factors. This innovative system integrates the dual influence of engineering effectiveness and natural factors, and incorporates building impact resistance assessment, significantly improving early warning accuracy. It is particularly suitable for progressive disaster prediction in areas with intensive engineering activities. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the system composition according to the first embodiment of this application;

[0039] Figure 2 This is a schematic diagram illustrating the working steps of the human activity correction unit according to the first embodiment of this application.

[0040] Figure 3 This is a schematic diagram illustrating the increased looseness of the soil surface caused by the plant roots being swept away by a debris flow, according to the first embodiment of this application. Detailed Implementation

[0041] The two embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0042] First implementation method:

[0043] Figure 1 A geological disaster monitoring and early warning system is shown, including a monitoring module, a historical storage module, an analysis and judgment module, an early warning module, and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the early warning level and notify the early warning level through the early warning module. The historical storage module is used to store the monitoring data of the monitoring module, and the simulation module is used to simulate the path and speed of debris flow disasters.

[0044] The monitoring module is used to collect environmental parameters of the area to be monitored and warned, including precipitation monitoring unit, vegetation monitoring unit, soil mobility monitoring unit, ground fissure monitoring unit and human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the area to be monitored.

[0045] The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit. The preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module, and the risk dynamic correction unit performs dynamic correction of the risk of the current warning based on the previous warning.

[0046] The human activity monitoring unit includes above-ground engineering monitoring units and underground engineering monitoring units. The above-ground engineering monitoring units are used to monitor the types and distribution areas of buildings on the surface of the area to be monitored and warned, while the underground engineering monitoring units are used to monitor the types and distribution areas of underground construction projects in the area to be monitored.

[0047] Specifically, in this application, the analysis and judgment module is used to calculate the degree of disaster early warning risk in the monitored area that may be caused by the environmental parameters collected by the monitoring module, and the monitoring module will monitor the precipitation, soil mobility, ground fissures, vegetation and human activities in the monitored area accordingly, thereby carrying out corresponding disaster early warning monitoring.

[0048] The calculation formula for the preliminary analysis unit is as follows:

[0049] R = R(p)*0.2 + R(w)*0.4 + R(g)*0.15 + R(f)*0.1 + R(h)*0.15, where R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. During the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.1. During the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.25.

[0050] The formula for calculating R(p) is as follows:

[0051] R(p)=E*(1-a*C*Rd*Rm*T)+b*C*Ra*max(0,τ-T 修) ,

[0052] T 修 =T0*(1-0.2*M),

[0053] E represents the basic risk of debris flow without vegetation cover, a and b are calibration coefficients, C is the vegetation cover rate of the area to be tested, and R... d R represents the root density of the plants in the area to be tested. m denoted as the average root depth of the area to be tested, T0 as the initial root tensile strength of the area to be tested, Ra as the lateral distribution radius of the roots in the area to be tested, and τ as the debris flow shear stress, where M is the soil saturation.

[0054] Specifically, in existing technologies, vegetation plays a positive role in mitigating debris flow warnings (because the soil-stabilizing effect of plants can reduce soil mobility, thereby reducing the impact of debris flows). However, in practice, some plants are deep-rooted or bamboo-like, whose root systems spread widely during growth and increase the loosening of the soil surface. When these plants are swept away by debris, the pulling and tugging of their roots further loosens the soil, thus increasing the severity of the debris flow (due to the rapid reproduction of underground stems, forming a dense root network that disrupts the original soil consolidation; deep-rooted plants, during their accelerated growth in spring, extend their roots outwards, compressing the soil structure, especially in clay or soft soil layers, easily causing ground cracking; bamboo shoots, when they emerge from the soil in spring, grow extremely fast (some varieties can grow tens of centimeters in a day), and their strong growth force can push open the soil, causing the ground to heave and crack). Figure 3 (As shown).

[0055] Based on the above explanation, it is necessary to take into account the root system of the plant. When debris flow or landslide disasters occur, the loose soil areas caused by plant growth and the areas where the root system is distributed should be considered. The loose soil areas caused by the plant being pulled out will increase the degree of debris flow. Therefore, R(p) is designed to adjust the accuracy of debris flow early warning risk analysis.

[0056] The formula for calculating R(h) is as follows:

[0057] R(h) = 1 - + ,in Let At represent the efficiency coefficient of the above-ground works of type t, and At represent the coverage of the above-ground works of type t. This represents the risk gain factor for the j-th type of underground engineering project. Indicates the disturbance intensity of underground engineering of type j. The aboveground impact factor.

[0058] Specifically, the efficiency coefficient of above-ground engineering and the risk gain factor of underground engineering differ for different types of above-ground buildings. For example, η=0.2 in drainage ditches, η=0.15 in platforms, γ=0.3 in mines, and γ=0.25 in tunnels. The values ​​are adjusted according to the different types. Therefore, underground buildings will increase the risk of surface debris flows, while above-ground buildings can play a certain role in intercepting or diverting debris flows when they arrive (for example, drainage ditches can play a partial diversion role), thereby mitigating the risk.

[0059] The formula for calculating R(w) is as follows:

[0060] R(w) = w1 * R w2 +w3, where w1, w2 and w3 are empirical parameters, and R is the drought index;

[0061] R(g) = σtanϕ + D*(1-S), where σ is the effective normal stress, ϕ is the internal friction angle, D is the soil cohesion, and S is the looseness index.

[0062] R(f) = K*(1+F / Fmax)*∇h, where K is the matrix permeability coefficient (m / s), F is the fracture density in m / m², Fmax is the maximum fracture density threshold, and ∇h is the hydraulic gradient.

[0063] The early warning module includes an early warning signal sending unit and an escape guidance unit. The early warning signal sending unit sends an early warning signal when the level of early warning risk exceeds the safety threshold. The escape guidance unit sends an escape route at the same time as sending the early warning signal, based on the simulated disaster occurrence path and speed.

[0064] Specifically, the signal transmission unit and the guidance and avoidance unit can assist the early warning module in issuing effective early warning signals and corresponding escape routes.

[0065] Figure 2 As shown, the monitoring module also includes a human activity correction unit, whose operating steps are as follows:

[0066] S1, the distance L between the above-ground buildings along the disaster path and the disaster occurrence point;

[0067] S2. Calculate whether the energy carried by the debris flow will damage the buildings when the disaster reaches the coordinates of the buildings on the ground;

[0068] S3. If no damage is caused. If positive, otherwise Multiply by (-1).

[0069] The impact resistance of above-ground structures in S2 is N = ζ*(fc*Aw / Ek)*e -k*L Where ζ is the structural type correction factor, fc is the compressive strength of the main building structure, Aw is obtained through BIM database or material testing, Aw is the effective shear area of ​​the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance of the building from the debris flow initiation point, and k is the terrain attenuation factor.

[0070] Specifically, when a building is under construction (not yet completed) or completed but small in size, the energy N at the location of the building is insufficient to resist the impact potential energy of a debris flow. The building will be destroyed during subsequent debris flow impacts and then carried into the debris flow, causing the debris flow to grow and thus increasing its harmfulness. Therefore, the value of N (h) needs to be positive at this time to increase the value of R (h) (including during the initial construction period, materials piled on the ground will also be carried into the subsequent debris flow, thus increasing the degree of debris flow warning risk).

[0071] Second implementation method:

[0072] Figure 2 The risk dynamic correction unit is shown to be used to dynamically correct situations where no disaster occurred after the previous warning signal was issued, and the risk level in the preliminary analysis unit does not exceed the safety threshold during the current warning monitoring, but the previous warning characteristics have not yet returned to zero, and there is a potential superimposed threat. The calculation formula is as follows:

[0073] R t修 =R t α*R t−1 + ;

[0074] R t This is the risk value obtained from preliminary analysis and calculation at the current moment;

[0075] R t修 This is the revised overall risk value for the current moment;

[0076] α: Time decay coefficient, α=e −λΔt λ is the decay rate, and Δt is the time interval;

[0077] β i The weight of the i-th controlling factor satisfies ∑β i =1);

[0078] f(x i ): The normalized contribution function f(x) of the i-th controlling factor i ) = (x i -L i ) / (U i -L i ), U i and L i These are the lower and upper limits of the threshold, respectively.

[0079] Unlike the first implementation method, where the calculation of debris flow early warning risk is usually a single, independent calculation, in practice, a warning signal may be issued in the previous round of early warning analysis but no disaster actually occurs. However, there may still be a high probability of debris flow disaster in the monitored area. If the next round of risk monitoring is judged to be an independent risk monitoring operation, and is subject to the residual threat of the previous warning (which has not yet been metabolized and decayed to a safe state), even if the calculated risk level is lower than the safety threshold, there is still a possibility that the disaster warning may exceed the safety threshold.

[0080] Specifically, if, based on the previous round of disaster warnings exceeding the safety threshold, during the next round of disaster monitoring, some factors (such as rainfall intensity) are below the safety threshold, while other factors have the same values ​​as in the previous round of monitoring, the potential for disaster will also occur due to the higher potential of the previous round of disasters. This is because the previous round of disasters had a higher potential level. The superimposed influencing factors (such as rainfall intensity, which will turn the previously precarious disaster threat into a real one) will also cause the potential for disasters to occur.

[0081] Therefore, it is designed with attenuation calculation and main control factors to avoid the continued impact of historical false alarms through time attenuation, and can adapt to different geological backgrounds, thereby improving the accuracy of disaster early warning.

[0082] In summary, the system achieves accurate early warning through multi-module collaboration. It includes a monitoring module for collecting data on precipitation, vegetation, soil, ground fissures, and human activities; an analysis and judgment module with preliminary analysis and dynamic correction units; an early warning module for sending alarms and providing escape routes; and a simulation module for predicting disaster paths. Among these, vegetation monitoring not only considers soil stabilization but also incorporates the root damage effect (deep-rooted plants may exacerbate soil loosening); human activity monitoring distinguishes between above-ground projects (such as drainage ditches that reduce risk) and underground projects (such as mines that increase risk); and the dynamic correction unit addresses the impact of residual risks from historical early warnings on current assessments through time decay and the superposition of key control factors. This system innovatively integrates the dual influence of engineering effectiveness and natural factors and introduces building impact resistance assessment, significantly improving early warning accuracy. It is particularly suitable for progressive disaster prediction in areas with intensive engineering activities.

[0083] In light of current practical needs, the above-described embodiments adopted in this application are not limited to these. Any changes made within the scope of knowledge possessed by those skilled in the art without departing from the concept of this application still fall within the protection scope of this invention.

Claims

1. A geological disaster monitoring and early warning system, characterized in that: It includes a monitoring module, a historical storage module, an analysis and judgment module, an early warning module, and a simulation module. The analysis and judgment module is used to collect data from the monitoring module to analyze the early warning level and notify the early warning level through the early warning module. The historical storage module is used to store the monitoring data of the monitoring module. The simulation module is used to simulate the path and speed of debris flow disasters. The monitoring module is used to collect environmental parameters of the area to be monitored and warned, including precipitation monitoring unit, vegetation monitoring unit, soil mobility monitoring unit, ground fissure monitoring unit and human activity monitoring unit. The vegetation monitoring unit is used to monitor the vegetation type, distribution area and season corresponding to the monitoring time point in the area to be monitored. The analysis and judgment module includes a preliminary analysis unit and a risk dynamic correction unit. The preliminary analysis unit is used to perform a preliminary analysis of the warning level based on the data collected by the monitoring module. The risk dynamic correction unit performs dynamic correction of the risk of the current warning based on the previous warning. The human activity monitoring unit includes a surface engineering monitoring unit and an underground engineering monitoring unit. The surface engineering monitoring unit is used to monitor the type and distribution of buildings on the surface of the area to be monitored and warned, and the underground engineering monitoring unit is used to monitor the type and distribution of underground construction projects in the area to be monitored. The calculation formula for the preliminary analysis unit is as follows: R(p) is the risk coefficient corresponding to the vegetation monitoring unit, R(w) is the risk coefficient corresponding to the precipitation monitoring unit, R(g) is the risk coefficient corresponding to the soil mobility monitoring unit, R(f) is the risk coefficient corresponding to the ground fissure monitoring unit, and R(h) is the risk coefficient corresponding to the human activity monitoring unit. During the rainy season, the weight of R(w) increases to 0.5 and the weight of R(p) decreases to 0.

1. During the dry season, the weight of R(h) increases to 0.3 and the weight of R(w) decreases to 0.

25. The formula for calculating R(h) is as follows: R(h) = 1 - ,in Let At represent the efficiency coefficient of the above-ground works of type t, and At represent the coverage of the above-ground works of type t. This represents the risk gain factor for the j-th type of underground engineering project. Indicates the disturbance intensity of underground engineering of type j. The aboveground impact factor; The risk dynamic correction unit is used to dynamically correct situations where no disaster occurred after the previous warning signal was issued, and the risk level in the preliminary analysis unit does not exceed the safety threshold during the current warning monitoring, but the previous warning characteristics have not yet returned to zero, and there is a potential superimposed threat. The calculation formula is as follows: ； R t This is the risk value obtained from preliminary analysis and calculation at the current moment; R t修 This is the revised overall risk value for the current moment; α: Time decay coefficient, α=e -λΔt λ is the decay rate, and Δt is the time interval; β i The weight of the i-th controlling factor satisfies ∑β i =1); f(x i ): The normalized contribution function f(x) of the i-th controlling factor i ) = (x i -L i ) / (U i -L i ), U i and L i These are the lower and upper limits of the threshold, respectively. The monitoring module also includes a human activity correction unit, whose operating steps are as follows: S1, the distance L between the above-ground buildings along the disaster path and the disaster occurrence point; S2. Calculate whether the energy carried by the debris flow will damage the buildings when the disaster reaches the coordinates of the buildings on the ground; S3. If no damage is caused. If positive, otherwise Multiply by (-1); The impact resistance of the above-ground buildings in S2 Where ζ is the structural type correction factor, fc is the compressive strength of the main building structure, Aw is obtained through BIM database or material testing, Aw is the effective shear area of ​​the building's frontal surface, Ek is the kinetic energy of the debris flow disaster, L is the horizontal distance of the building from the debris flow initiation point, and k is the terrain attenuation factor.

2. The geological disaster monitoring and early warning system according to claim 1, characterized in that: The formula for calculating R(p) is as follows: ， ， E represents the basic risk of debris flow without vegetation cover, a and b are calibration coefficients, C is the vegetation cover rate of the area to be tested, and R... d R represents the root density of the plants in the area to be tested. m denoted as the average root depth of the area to be tested, T0 as the initial root tensile strength of the area to be tested, Ra as the lateral distribution radius of the roots in the area to be tested, and τ as the debris flow shear stress, where M is the soil saturation.

3. The geological disaster monitoring and early warning system according to claim 1, characterized in that: The formula for calculating R(w) is as follows: , where w1, w2 and w3 are empirical parameters, and R is the drought index; Where σ is the effective normal stress, Where is the internal friction angle, D is the soil cohesion, and S is the looseness index; Where K is the matrix permeability coefficient (m / s), F is the fracture density in m / m², and Fmax is the maximum fracture density threshold. This represents the hydraulic gradient.

4. A geological disaster monitoring and early warning system according to claim 1, characterized in that: The early warning module includes an early warning signal sending unit and an escape guidance unit. The early warning signal sending unit sends an early warning signal when the level of early warning risk exceeds a safety threshold. The escape guidance unit sends an escape path at the same time as sending the early warning signal, based on the simulated disaster occurrence path and speed.

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