Ground subsidence prediction method based on three-dimensional monitoring network

Abstract

The invention belongs to the technical field of land subsidence monitoring and early warning, and relates to a land subsidence prediction method based on a three-dimensional monitoring net, which comprises the following steps: S1, generalizing a hydrogeological structure and quantifying the volume compression coefficient of each layer based on test data of a geological identification hole and observation data of an underground water level monitoring hole, a layered standard hole and a pore water pressure monitoring hole; s2, constructing a three-dimensional groundwater seepage model, and calculating groundwater level spatial distribution data of each aquifer; s3, fitting observation data of the underground water level monitoring hole with a calculation result, and inverting parameters in the three-dimensional underground water seepage model; and S4, operating the inverted groundwater seepage model to obtain groundwater level drawdown and pore water pressure difference spatial distribution data and the like of each water-bearing layer and each water-resisting layer. According to the land subsidence prediction method provided by the invention, the severity of land subsidence can be effectively, quickly and visually judged, the prediction result is high in precision, and land subsidence prediction caused by exploiting underground water at different depths is supported.

Description

Technical Field

[0001] The invention belongs to the technical field of ground subsidence monitoring and early warning, and relates to a ground subsidence prediction method based on a three-dimensional monitoring network. Background Art

[0002] At present, InSAR, ground markers, layered marker groups, fuzzy hierarchical analysis method, machine learning algorithms and other means are commonly used for subsidence monitoring, analysis and prediction. However, in the application process, only one or two of them are mainly used, and the coordination and complementation between different technologies are insufficient. Moreover, subsidence monitoring can only reflect single-point or local subsidence changes. In addition to being unable to display the temporal and spatial distribution of ground subsidence in the overall area, it also lacks the problem of dynamic changes of ground subsidence from a development perspective. Summary of the invention

[0003] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a ground subsidence prediction method based on a three-dimensional monitoring network.

[0004] In order to achieve the above object, the present invention provides the following technical solutions: A method for predicting land subsidence based on a three-dimensional monitoring network, comprising: S1, generalize the hydrogeological structure and quantify the volume compression coefficient of each layer based on the experimental data of geological identification holes and the observation data of groundwater level monitoring holes, stratification marking holes, and pore water pressure monitoring holes; S2, construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of groundwater levels in each aquifer; S3, fitting the observation data of groundwater level monitoring holes with the calculation results, inverting the parameters in the three-dimensional groundwater seepage model; S4, running the inverted groundwater seepage model to obtain the groundwater level drawdown and pore water pressure difference spatial distribution data of each aquifer and aquitard; S5, under one-dimensional nonlinear consolidation conditions, the deformations caused by the water level difference or pore water pressure difference at different spatial positions are superimposed to obtain the final ground settlement value.

[0005] In the present invention, preferably, S1 comprises: S11, based on the test data of the geological identification hole, determine the distribution of stratum grain size and divide the lithology layer of the entire well section, wherein the test data of the geological identification hole includes geophysical logging data, geological columnar diagram and core test data; S12 uses the equivalent permeability coefficient method to draw the cumulative change curve of water conductivity with depth, combines the lithology layers of the entire well section according to the change of the slope of the curve, and generalizes the spatial distribution of the water-bearing medium in the site, including quantifying the burial depth, thickness and permeability zoning of the aquifer and aquiclude; S13, according to the formula of the final settlement of the top surface of the one-dimensional nonlinear finite strain consolidation of the soil layer: The formula for the volume compression coefficient of the soil skeleton is derived as follows: Where m v is the volume compression coefficient of the soil skeleton, S is the final settlement of the top surface of the corresponding soil layer, H is the thickness of the aquifer or aquiclude, q u is the vertical stress change caused by the water pressure change, q u = ×S w ,in is the water density, S w To correspond to the change of soil water level or pore water pressure; S14, based on the measured groundwater level drop data, pore water pressure difference data, and top surface settlement data of each layer within the same time period, the volume compression coefficient formula of the soil skeleton is used to solve the volume compression coefficient of each aquifer and aquiclude.

[0006] In the present invention, preferably, the aquifer described in S12 refers to a stratum composed of at least one medium selected from gravel, sand and silt that can give out and pass water.

[0007] In the present invention, preferably, the aquiclude described in S12 refers to a stratum composed of at least one medium selected from clay and silty clay that can neither pass nor deliver water.

[0008] In the present invention, preferably, S2 includes: S21, establish a hydrogeological structure model based on the quantified burial depth of aquifers and impermeable layers and the permeability zoning of each layer; S22, input the permeability coefficient, water supply degree, elastic water release rate, recharge volume, and extraction volume into the hydrogeological structure model; S23, calculate the spatial contour map of groundwater levels in each aquifer on the site.

[0009] In the present invention, preferably, the method of inverting the parameters in the three-dimensional groundwater seepage model in S3 is: Compare the deviation between the calculated groundwater level value and the observed groundwater level value of the site, and repeatedly run the model by continuously adjusting the values ​​of the permeability coefficient, water supply degree, and elastic water release rate until the calculated groundwater level value and the observed groundwater level value trend can be completely fitted, and the root mean square error is no more than 2%. At this time, the parameters in the model are the hydrogeological parameters suitable for this site.

[0010] In the present invention, preferably, the planned extraction volume under different rainfall environments is substituted into the inverted groundwater seepage model in S4, and the inverted groundwater seepage model is run to obtain the groundwater level drop values ​​or pore water pressure differences at different spatial positions.

[0011] In the present invention, preferably, the different rainfall environments refer to the dry season, the flood season, the normal water season and the average rainfall period over N years.

[0012] In the present invention, preferably, S5 includes: S51, export the groundwater level difference or pore water pressure difference data of each layer after the model is run, and the exported data is arranged in the format of X, Y, S w Under one-dimensional nonlinear consolidation conditions, the final ground settlement values ​​at different spatial positions are calculated using the layered summation method. The calculation formula is as follows: Where S 总 is the final surface settlement value; H i is the thickness of the i-th layer of water-containing medium; q ui is the vertical stress change caused by the water pressure change of the i-th layer of water-bearing medium, q ui = ×S wi ,in is the water density, S wi is the change of water level or pore water pressure of the i-th layer of water-bearing medium; m vi is the volume compression coefficient of the i-th layer of water-bearing soil skeleton, X and Y are plane coordinates, S w It is the change of water level or pore water pressure in aquiferous medium; S52, importing the final ground settlement values ​​at different spatial locations into the geographic data gridding drawing software Sufer to obtain a ground settlement contour map within the site.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention introduces the three-dimensional monitoring network technology of ground subsidence and the one-dimensional nonlinear finite strain consolidation principle of soil layers, which effectively improves the accuracy of ground subsidence prediction. The present invention uses groundwater seepage simulation technology to obtain the dynamic spatiotemporal change values ​​of groundwater levels under different conditions, and then intuitively displays the spatiotemporal distribution characteristics of ground subsidence. It has strong guidance, facilitates the adoption of targeted anti-sinking measures, and saves disaster prevention time and economic costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The present invention is a flowchart of a method for predicting ground subsidence based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0015] Figure 2This is a flowchart of S1 in the ground subsidence prediction method based on a three-dimensional monitoring network in an embodiment of the present invention.

[0016] Figure 3 This is a flowchart of S2 in the ground subsidence prediction method based on a three-dimensional monitoring network in an embodiment of the present invention.

[0017] Figure 4 This is a flowchart of S5 in the ground subsidence prediction method based on a three-dimensional monitoring network according to an embodiment of the present invention.

[0018] Figure 5 It is the upper half of the comprehensive column chart of the geological identification hole of a certain site in the embodiment of the present invention.

[0019] Figure 6 It is the lower half of the comprehensive column chart of the geological identification hole of a certain site in the embodiment of the present invention.

[0020] Figure 7 This is a curve diagram of the cumulative water conductivity of a geological identification hole at a certain site as a function of depth according to an embodiment of the present invention.

[0021] Figure 8 This is a grid division of a groundwater seepage model and a calculated groundwater level distribution map for a site in an embodiment of the present invention, with a scale of 1:1000.

[0022] Fig. 9 This is a fitting comparison diagram of the calculated groundwater level and the observed groundwater level in a certain field of an embodiment of the present invention, with a scale of 1:1000.

[0023] Fig.10 This is a spatial distribution map of the groundwater level drop at a site in an embodiment of the present invention after 10 years of current groundwater exploitation under an average rainfall environment of N years, with a scale of 1:1000.

[0024] Fig.11 This is a spatial distribution map of ground subsidence at a site in an embodiment of the present invention after 10 years of current groundwater exploitation under an average rainfall environment of N years, with a scale of 1:1000. DETAILED DESCRIPTION

[0025] 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, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0026] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0027] Please also see Figures 1 to 4 A preferred embodiment of the present invention provides a method for predicting land subsidence based on a three-dimensional monitoring network, comprising: S1, based on the experimental data of geological identification holes and the observation data of groundwater level monitoring holes, stratification marking holes, and pore water pressure monitoring holes, the hydrogeological structure is generalized and the volume compression coefficient of each layer is quantified.

[0028] Specifically, Figure 2 As shown, the generalized hydrogeological structure and quantified volume compression coefficient of each layer in S1 may include: S11, based on the test data of the geological identification hole (including geophysical logging data, geological columnar diagram and core test data), determine the distribution of stratum grain size and divide the lithology layers of the entire well section.

[0029] like Figure 5 and Figure 6 As shown in the comprehensive column chart of the geological identification hole of a certain site, the distribution of stratum grain size, burial depth of different lithologies, porosity and permeability are identified through the geophysical logging data in the geological identification hole, combined with the coring of the entire well section and the local hydrogeological data.

[0030] S12, the equivalent permeability coefficient method is used to draw the cumulative change curve of water conductivity with depth. According to the change of the slope of the curve, the lithology layers of the entire well section are combined to generalize the spatial distribution of the water-bearing medium in the site, including the quantification of the burial depth, thickness and permeability zoning of the aquifer and aquiclude.

[0031] Aquifers refer to strata that can give out and permeate water and are composed of at least one of gravel, sand, and silt, while aquicludes refer to strata that can neither give out nor permeate water and are composed of at least one of clay and silty clay. Figure 7 The cumulative water conductivity of the geological identification hole of a site varies with depth, as shown in the curve. By calculating the product of the lithology permeability coefficient of each layer of the geological identification hole and the layer thickness, and accumulating The cumulative hydraulic conductivity is obtained, and a curve of cumulative hydraulic conductivity versus depth is plotted. Figure 7 It can be seen that the slope of the curve changes significantly with depth. A large slope indicates good permeability, which can be generalized as an aquifer, while a small slope indicates poor permeability, which can be generalized as an impermeable layer. According to the slope change trend of the curve, the water-bearing medium of the geological identification hole is generalized into 5 layers. The horizontal permeability coefficient of each layer of water-bearing medium can be calculated using the following formula: Where: K h is the generalized horizontal permeability coefficient of the water-bearing rock group (m / d); K hi is the horizontal permeability coefficient of the ith formation (m / d); M i is the thickness of the ith stratum (m).

[0032] S13, according to the formula of the final settlement of the top surface of the one-dimensional nonlinear finite strain consolidation of the soil layer: The formula for the volume compression coefficient of the soil skeleton is derived as follows: Where m v is the volume compression coefficient of the soil skeleton; S is the final settlement of the top surface of the corresponding soil layer; H is the thickness of the aquifer or aquiclude; q u is the vertical stress change caused by the water pressure change, q u = ×S w ,in is the water density, S w It corresponds to the change of soil water level or pore water pressure.

[0033] S14, based on the measured water level drop data, pore water pressure difference data, and settlement data of the top surface of each layer within the same time period, the volume compression coefficient formula of the soil skeleton is used to solve the volume compression coefficient of each aquifer and aquiclude.

[0034] As shown in Table 1 below, by reading the relevant data of groundwater level monitoring holes, stratified marking holes, and pore water pressure monitoring holes, the water level drop data, pore water pressure difference data, and top surface settlement data of each layer in the same time period are obtained, and the volume compression coefficients of soil layer skeletons of different water-containing media are obtained by substituting them into the volume compression coefficient solution formula of the above-mentioned soil layer skeleton.

[0035] Table 1 Calculation process of volume compression coefficient of different aqueous media S2, construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of groundwater levels in each aquifer.

[0036] Specifically, Figure 3 As shown, S2 includes: S21. Establish a hydrogeological structure model based on the quantified burial depth of aquifers and impermeable layers and the permeability zoning of each layer.

[0037] S22, input the permeability coefficient, water supply degree, elastic water release rate, recharge volume and extraction volume into the hydrogeological structure model.

[0038] S23, calculate the spatial contour map of groundwater levels in each aquifer on the site.

[0039] like Figure 8 As shown in the figure, based on the quantified burial depth of aquifers and impermeable layers and the permeability zoning of each layer, a hydrogeological structure model is established. The data of permeability coefficient, water supply degree, elastic water release rate, recharge volume, and extraction volume are input into the model to obtain a three-dimensional groundwater seepage model. This model is solved by the discretization method to obtain the groundwater level contour map of the site (i.e. Figure 8 solid line with data in the middle).

[0040] S3, fitting the observation data of groundwater level monitoring holes with the calculation results, and inverting the parameters in the three-dimensional groundwater seepage model.

[0041] Specifically, the deviation between the calculated groundwater level and the observed groundwater level is compared, and the values ​​of permeability coefficient, water supply degree, and elastic water release rate are continuously adjusted, and the model is repeatedly run until the calculated groundwater level and the observed groundwater level (the observed value of the groundwater level monitoring hole) can be fully fitted. Fig. 9 It is a comparison chart between the calculated groundwater level contour map (solid line) and the observed groundwater level contour map (dashed line) of a site including a geological identification hole. It can be seen that the calculated groundwater level contour map fits the macroscopic morphology well, not only correctly reflects the recharge and drainage characteristics of groundwater, but also has a high fitting accuracy with the measured water level values ​​in most areas, with an absolute error of less than 1m, and the root mean square error also meets the research requirements, that is, the root mean square error is no more than 2%. At this time, the parameters in the model are the hydrogeological parameters suitable for this site.

[0042] S4, run the inverted groundwater seepage model to obtain the spatial distribution data of groundwater level drawdown and pore water pressure difference in each aquifer and aquitard.

[0043] Changes in groundwater level or pore water pressure cause changes in the vertical stress of each soil layer in the site, which in turn induces ground subsidence. The dynamic change of water level is affected by rainfall and local groundwater extraction. According to the abundance of rainfall, the rainfall environment is divided into several specific rainfall periods: dry season, flood season, normal season and N-year average. The N-year average rainfall period is a rainfall data obtained through calculation, and N years can be a number of years set arbitrarily according to needs.

[0044] Specifically, the planned extraction volume under different rainfall environments is substituted into the inverted groundwater seepage model, and the spatial distribution data of groundwater level drop and / or pore water pressure difference of each aquifer and aquitard are obtained. Fig.10 As shown in the figure, it is the spatial distribution map of groundwater level drop calculated after 10 years of groundwater exploitation at a site containing geological identification holes under the current development under the average rainfall environment of N years.

[0045] S5, under one-dimensional nonlinear consolidation conditions, the deformations caused by the water level difference or pore water pressure difference at different spatial positions are superimposed to obtain the final ground settlement value.

[0046] Specifically, Figure 4 As shown, the calculation of the final ground settlement values ​​at different spatial positions in S5 may include S51, export the groundwater level difference or pore water pressure difference data of each layer after the model is run, and the exported data is arranged in the format of X, Y, S w Under one-dimensional nonlinear consolidation conditions, the final ground settlement values ​​at different spatial positions are calculated using the layered summation method. The calculation formula is as follows: Where S 总 is the final ground settlement value; H i is the thickness of the i-th layer of water-containing medium; q ui is the vertical stress change caused by the water pressure change of the i-th layer of water-bearing medium, q ui = ×S wi ,in is the water density, S wi is the change of water level or pore water pressure of the i-th layer of water-bearing medium; m vi is the volume compression coefficient of the i-th layer of water-bearing soil skeleton, X and Y are plane coordinates, S w It is the water level change of the water-bearing medium or the change of pore water pressure. When the location is an aquifer, the water level change of the water-bearing medium is measured, that is, S w Indicates the water level change of the aquifer (or the water level difference of the aquifer). When the location is an impermeable layer, the pore water pressure change is measured, that is, S w Represents the change in pore water pressure (or pore water pressure difference).

[0047] S52, import the final ground settlement values ​​at different spatial locations into the geographic data gridding drawing software Surfer to obtain the ground settlement contour map within the site. Fig.11 As shown, the severity of ground subsidence can be effectively, quickly and intuitively judged.

Claims

1. A method for predicting land subsidence based on a three-dimensional monitoring network, characterized in that: include: S1, generalize the hydrogeological structure and quantify the volume compression coefficient of each layer based on the experimental data of geological identification holes and the observation data of groundwater level monitoring holes, stratification marking holes, and pore water pressure monitoring holes; S2, construct a three-dimensional groundwater seepage model and calculate the spatial distribution data of groundwater levels in each aquifer; S3, fitting the observation data of groundwater level monitoring holes with the calculation results, inverting the parameters in the three-dimensional groundwater seepage model; S4, running the inverted groundwater seepage model to obtain the groundwater level drawdown and pore water pressure difference spatial distribution data of each aquifer and aquitard; S5, under one-dimensional nonlinear consolidation conditions, the deformations caused by the water level difference or pore water pressure difference at different spatial positions are superimposed to obtain the final ground settlement value.

2. The method according to claim 1, characterized in that The S1 includes: S11, based on the test data of the geological identification hole, determine the distribution of stratum grain size and divide the lithology layer of the entire well section; the test data of the geological identification hole includes geophysical logging data, geological columnar diagram and core test data; S12, using the equivalent permeability coefficient method to draw the cumulative change curve of water conductivity with depth, combining the lithology layers of the entire well section according to the change of the slope of the curve, generalizing the spatial distribution of the water-bearing media in the site, including quantifying the burial depth, thickness and permeability zoning of the aquifer and aquiclude; S13, according to the formula of the final settlement of the top surface of the one-dimensional nonlinear finite strain consolidation of the soil layer: The formula for the volume compression coefficient of the soil skeleton is derived as follows: Where m v is the volume compression coefficient of the soil skeleton, S is the final settlement of the top surface of the corresponding soil layer, H is the thickness of the aquifer or aquiclude, q u is the vertical stress change caused by the water pressure change, q u = ×S w ,in is the water density, S w To correspond to the change of soil water level or pore water pressure; S14, based on the measured water level drop data, pore water pressure difference data, and settlement data of the top surface of each layer within the same time period, the volume compression coefficient formula of the soil skeleton is used to solve the volume compression coefficient of each aquifer and aquiclude.

3. The method according to claim 2, characterized in that The aquifer refers to a stratum composed of at least one medium selected from gravel, sand and silt that can give out and pass water.

4. The method according to claim 2, characterized in that: The aquiclude refers to a stratum composed of at least one medium selected from clay and silty clay that can neither give out nor pass through water.

5. The method according to claim 1, characterized in that The S2 includes: S21, establish a hydrogeological structure model based on the quantified burial depth of aquifers and impermeable layers and the permeability zoning of each layer; S22, input the permeability coefficient, water supply degree, elastic water release rate, recharge volume, and extraction volume into the hydrogeological structure model; S23, calculate the spatial contour map of groundwater levels in each aquifer on the site.

6. The method according to claim 1, characterized in that The method of inverting the parameters in the three-dimensional groundwater seepage model in S3 is: Compare the deviation between the calculated groundwater level value and the observed groundwater level value of the site, and repeatedly run the model by continuously adjusting the values ​​of the permeability coefficient, water supply degree, and elastic water release rate until the calculated groundwater level value and the observed groundwater level value trend can be completely fitted, and the root mean square error is no more than 2%. At this time, the parameters in the model are the hydrogeological parameters suitable for this site.

7. The method according to claim 1, characterized in that In S4, the planned extraction volume under different rainfall environments is substituted into the inverted groundwater seepage model, and the inverted groundwater seepage model is run to obtain groundwater level drop values ​​or pore water pressure difference values ​​at different spatial positions.

8. The method according to claim 7, characterized in that The different rainfall environments refer to the dry season, the flood season, the normal water season and the average rainfall period over N years.

9. The method according to claim 1, characterized in that: The S5 includes: S51, export the groundwater level difference or pore water pressure difference data of each layer after the model is run, and the exported data is arranged in the format of X, Y, S w Under one-dimensional nonlinear consolidation conditions, the final ground settlement values ​​at different spatial positions are calculated using the layered summation method. The calculation formula is as follows: ， in S 总 is the final ground settlement value, H i is the thickness of the i-th layer of water-containing medium, q ui is the vertical stress change caused by the water pressure change of the i-th layer of water-bearing medium, q ui = ×S wi ,in is the water density, S wi is the change in water level or pore water pressure of the i-th layer of water-bearing medium, m vi is the volume compression coefficient of the i-th layer of water-bearing soil skeleton, X and Y are plane coordinates, S w It is the change of water level or pore water pressure in aquiferous medium; S52, importing the final ground settlement values ​​at different spatial locations into the geographic data gridding drawing software Sufer to obtain a ground settlement contour map within the site.

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