Radon tracing-multi-field coupling river bank karst collapse dynamic early warning method

Abstract

The invention discloses a radon tracing-multi-field coupling river bank karst collapse dynamic early warning method, and belongs to the field of geological disaster monitoring and early warning. The method comprises the following steps: collecting radon concentration data of river water and underground water on both sides along a target river reach system by using a portable radon detector; calculating underground water discharge flux based on the radon concentration data, and generating a discharge flux distribution diagram through spatial interpolation; establishing a radon isotope-seepage-subsurface erosion-mechanical stability multi-field coupling model; based on the multi-field coupling model, calculating karst collapse stability coefficients under different water exchange intensities; determining the variable amplitude of the critical river water level as an early warning threshold value, and dividing risk grades; and dynamic early warning and graded prevention and control based on river water level monitoring are implemented. The radon isotope tracing technology and the multi-field coupling model are combined and applied to karst collapse early warning for the first time. A complete disaster-causing chain of river water level fluctuation, water exchange enhancement, subsurface erosion development, permeability increase and sudden collapse is disclosed.

Description

TECHNICAL FIELD

[0001] The present application relates to geological disaster monitoring and early warning, and in particular to a riverbank karst collapse dynamic early warning method based on radon tracing and multi-field coupling. BACKGROUND

[0002] In the urban coastal zone, especially in the area with "sand over rock" dual stratigraphic structure (such as the Yangtze River coast and the abandoned Yellow River coast in Xuzhou), the frequent fluctuation of river water level drives the strong exchange between river water and groundwater, which becomes the main driving force for inducing overburden karst collapse. However, the traditional collapse risk assessment method has obvious shortcomings: the spatial positioning is not accurate, it is difficult to economically and efficiently obtain the spatial distribution of water exchange intensity of a large range of coastlines, and it is difficult to identify "seepage dominant channel"; the mechanism is not complete, usually taking the absolute value of groundwater level as the early warning index, and the dynamic development process of potential erosion is not fully considered; the early warning index is not intuitive: it is difficult to convert the complex water-rock interaction into an engineering parameter that is easy to monitor and manage. SUMMARY

[0003] The purpose of the present application is to provide a method that can realize accurate positioning, quantitative evaluation and intuitive early warning of karst collapse, and convert complex geological processes into engineering indicators that are easy to manage.

[0004] Technical scheme: The riverbank karst collapse dynamic early warning method based on radon tracing and multi-field coupling comprises the following steps: S1, using a portable radon meter, systematically collecting radon concentration data of river water and groundwater on both banks along the target river section; S2, based on the radon concentration data, calculating the groundwater discharge flux and generating a discharge flux distribution map through spatial interpolation; S3, establishing a multi-field coupling model of radon isotope-seepage-potential erosion-mechanical stability; S4, based on the multi-field coupling model, calculating the karst collapse stability coefficient under different water exchange intensities; S5, determining the critical river water level amplitude as the early warning threshold, and dividing the risk level; S6, implementing dynamic early warning and hierarchical prevention and control based on river water level monitoring.

[0005] Further, the groundwater discharge flux in step S2 is calculated by the following formula:

[0006] wherein, Q gw is the discharge flux, R gw and R river is the radon concentration of groundwater and river water, λ is the radon decay constant,θ riverbed sediment porosity.

[0007] Further, the radon tracing-multiple field coupling riverbank karst collapse dynamic early warning method according to claim 1 is characterized in that the stability coefficient in step S4 is calculated by the following formula:

[0008] wherein, i cr is a critical hydraulic gradient, L is a seepage path length, Δh is a water head difference, η(t) is a permeability increasing coefficient, δ is a potential erosion influence empirical coefficient, and is valued at 0.05-0.15 according to the soil type and the potential erosion development degree.

[0009] Further, the critical river water level amplitude in step S5 is calculated by the following formula:

[0010] wherein, β is a local water head response coefficient obtained based on radon flux inversion.

[0011] A riverbank karst collapse early warning system realized by the above method comprises: a radon isotope monitoring module for radon concentration collection and data processing; a multiple field coupling analysis module for dynamic evaluation of karst collapse stability; an early warning decision module for determining an early warning threshold and issuing early warning information; a river water level real-time monitoring module for monitoring river water level changes.

[0012] Beneficial effects: (1) The radon isotope tracing technology is combined with the multiple field coupling model to be applied to karst collapse early warning for the first time. The complete disaster-causing chain of "river water level fluctuation→water exchange enhancement→potential erosion development→permeability increase→sudden collapse" is disclosed. A dynamic coupling model considering time variable is established to realize time-effective prediction of the collapse process.

[0013] (2) Simple operation: field data collection is fast and simple without the need for complex instruments and equipment; low cost: compared with traditional drilling and geophysical prospecting methods, the cost is significantly reduced; intuitive results: complex mechanisms are converted into easy-to-understand river water level early warning thresholds; strong adaptability: suitable for various "sand on top and rock below" binary structure areas.

[0014] (3) The application is verified by examples, and the spatial positioning is accurate: the newly born street section is successfully identified as a high-risk area, which is consistent with the actual collapse position; the threshold is scientific and reasonable: the critical river water level amplitude is calculated as 0.93 m, and the actual amplitude during the historical collapse is 5 m, far exceeding the threshold; the time limit for the prediction is accurate: the development process of potential erosion and the time window of collapse occurrence can be predicted in advance. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a method flowchart of the application. DETAILED DESCRIPTION

[0016] In order to make the technical scheme of the application clearer, the application will be further described in detail below in combination with the drawings and specific embodiments.

[0017] As shown in Figure 1 , the radon tracing-multiple field coupling riverbank karst collapse dynamic early warning method comprises: (1) Radon isotope patrol measurement and data processing Sampling network design: sampling points are arranged along the target river section according to gridding, including river water sampling points and groundwater sampling points.

[0018] On-site rapid determination: using a portable radon meter to determine the radon concentration (Rn-222) of the water sample on site.

[0019] Auxiliary parameter acquisition: simultaneously acquiring environmental parameters such as pore water pressure, water temperature, and electrical conductivity.

[0020] Spatial interpolation analysis: using the Kriging method to generate a groundwater discharge flux spatial distribution map.

[0021] (2) Multiple field coupling model construction The application establishes a radon isotope-seepage-potential erosion-mechanical stability multiple field coupling model: Water exchange intensity quantitative model, groundwater discharge calculation based on the principle of radon mass balance:

[0022] Among them, Q gw is the discharge flux, R gw and R river is the radon concentration of groundwater and river water, λ is the radon decay constant, θ is the riverbed sediment porosity.

[0023] Potential erosion development dynamics model, permeability dynamic change model:

[0024] Among them,η(t) is the permeability increase coefficient, α , β is the soil-related parameter. α : soil sensitivity parameter (fine sand: 0.8-1.2; coarse sand: 0.5-0.8), β : potential erosion rate parameter (0.1-0.5d -1 ).

[0025] Stability comprehensive evaluation model, complete stability coefficient calculation formula:

[0026] wherein, i cr is the critical hydraulic gradient, L is the seepage path length, Δh is the water head difference, δ is the potential erosion influence empirical coefficient, taking value 0.05-0.15 according to soil type and potential erosion development degree.

[0027] (3) Early warning threshold determination method Critical condition analysis: when K s (t)=1, the system is in a critical unstable state, and the corresponding river water level amplitude is the critical value.

[0028] Threshold calculation: determine the critical river water level amplitude by inversion analysis:

[0029] wherein, β is the local water head response coefficient obtained based on radon flux inversion. It is determined by the following method: Based on multi-period radon concentration and river water level monitoring data, through formula:

[0030] regression calculation; or based on geological analogy method, according to hydrogeological conditions, taking value in the following range: Strongly connected medium: 3.0-8.0; Medium connected medium: 1.5-3.0; Weakly connected medium: 0.5-1.5.

[0031] Risk level division: based on the relationship curve between radon concentration and stability coefficient, the risk is divided into: High risk: radon concentration 2000-5000Bq / m 3 , K s <0.4; Medium risk: radon concentration 5000-15000Bq / m 3 , K s= 0.4-0.7; Low risk: Radon concentration >15000 Bq / m 3 , K s >0.7.

[0032] Example: Karst collapse early warning of Xuzhou abandoned Yellow River Xinsheng Street section 1. Data collection and processing Sampling arrangement: 3 monitoring profiles were laid along the abandoned Yellow River Xinsheng Street section, with a total of 25 sampling points.

[0033] Radon concentration determination: The average measured river water radon concentration was 353 Bq / m 3 , and the groundwater radon concentration ranged from 2000 to 11000 Bq / m 3 .

[0034] Rock and soil parameters: critical hydraulic gradient i cr =0.99, permeability coefficient K=10 m / d, porosity θ=0.35.

[0035] 2. Application of multi-field coupling model Water exchange intensity evaluation: The calculated groundwater discharge flux ranged from 0.044 to 0.104 m / d, and the Xinsheng Street section was classified as a high risk area of intense exchange.

[0036] Stability dynamic evaluation: The stability coefficient was calculated using the coupling model: without considering water exchange: K s =0.876; considering water exchange: K s =0.25-0.59 (changes with radon concentration).

[0037] Early warning threshold determination: effective potential erosion path length: L local =5m; local water head response coefficient: β=5.3; critical river water level amplitude: ΔH cr =0.99×5 / 5.3≈0.93m.

[0038] 3. Early warning effect verification In 1992, the river section was dredged, resulting in a river level drop of about 5m, far exceeding the early warning threshold (0.93m), which actually triggered karst collapse, verifying the accuracy of the method.

[0039] 4. Prevention and control measures Based on the results of the invention, hierarchical prevention and control suggestions are proposed: High risk area (<5000 Bq / m 3 ): Strengthen monitoring, river level change >1.0m early warning.

[0040] Medium risk area (5000-15000 Bq / m 3): Regular monitoring, warning if river level changes > 2.0 m.

[0041] Low risk zone (> 15000 Bq / m 3 ): Regular monitoring, warning if river level changes > 3.0 m.

[0042] The above-described embodiments are merely representative of several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as limiting the scope of the patent of the present application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A dynamic early warning method for riverbank karst collapse based on radon tracing and multi-field coupling, characterized in that, Includes the following steps: S1. Use a portable radon meter to systematically collect radon concentration data of river water and groundwater on both banks along the target river section; S2. Based on the radon concentration data, calculate the groundwater discharge flux and generate a discharge flux distribution map through spatial interpolation; S3. Establish a multi-field coupled model of radon isotope-seepage-undercutting-mechanical stability; S4. Based on the multi-field coupling model, calculate the karst collapse stability coefficient under different water exchange intensities; S5. Determine the critical river water level fluctuation range as the early warning threshold and classify the risk levels; S6. Implement dynamic early warning and tiered prevention and control based on river water level monitoring.

2. The radon tracing-multi-field coupled dynamic early warning method for riverbank karst collapse according to claim 1, characterized in that, The groundwater discharge flux in step S2 is calculated using the following formula: in, Q gw To discharge flux, R gw and R river Radon concentration in groundwater and river water. λ Let be the radon decay constant. θ Porosity of riverbed sediments.

3. The radon tracing-multi-field coupled dynamic early warning method for riverbank karst collapse according to claim 1, characterized in that, The stability coefficient in step S4 is calculated using the following formula: in, i cr The critical hydraulic gradient, L This is the seepage path length. Δh Due to head difference, η(t) This is the permeability enhancement factor. δ The empirical coefficient for the impact of burrowing is 0.05-0.15, which is determined based on the soil type and the degree of burrowing development.

4. The radon tracing-multi-field coupled dynamic early warning method for riverbank karst collapse according to claim 3, characterized in that, The critical river water level fluctuation in step S5 is calculated using the following formula: in, β The local head response coefficient is obtained based on radon flux inversion.

5. A riverbank karst collapse early warning system implemented using the method described in any one of claims 1 to 4, characterized in that, include: Radon isotope monitoring module, used for radon concentration acquisition and data processing; A multi-field coupling analysis module is used to dynamically evaluate the stability of karst collapse; The early warning decision module is used to determine early warning thresholds and issue early warning information; The real-time river water level monitoring module is used to monitor changes in river water levels.

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