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CN111833208A - Underground water reserve monitoring method and system based on vertical deviation disturbance - Google Patents

Underground water reserve monitoring method and system based on vertical deviation disturbance Download PDF

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CN111833208A
CN111833208A CN202010673356.7A CN202010673356A CN111833208A CN 111833208 A CN111833208 A CN 111833208A CN 202010673356 A CN202010673356 A CN 202010673356A CN 111833208 A CN111833208 A CN 111833208A
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vertical deviation
deviation disturbance
disturbance
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CN111833208B (en
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李超超
刘伟铭
钱学武
沈翔
徐飞
曾凯
兰骧
于亦龙
吕志彬
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Ningxia University
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Abstract

The invention discloses a method and a system for monitoring underground water reserves based on vertical deviation disturbance. The underground water reserve monitoring method based on vertical deviation disturbance comprises the following steps: acquiring the running speed of a measuring carrier; constructing a vertical deviation disturbance two-order random process optimization model based on the driving speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; calculating a vertical deviation disturbance component based on a vertical deviation disturbance two-step random process optimization model; the vertical deviation disturbance component comprises a vertical deviation disturbance north-south component and a vertical deviation disturbance east-west component; and obtaining the underground water reserve variation of the area where the measurement carrier is located by inversion of the vertical deviation disturbance component. The invention solves the problem that large-scale and large-scale underground water data cannot be acquired, and improves the monitoring efficiency of underground water reserves.

Description

Underground water reserve monitoring method and system based on vertical deviation disturbance
Technical Field
The invention relates to the technical field of gravity measurement, in particular to a groundwater reserve monitoring method and system based on vertical deviation disturbance.
Background
With the development of socio-economy and the growth of population, the water consumption of industry and agriculture is increasing day by day, and the supply and demand of water resources used by human beings are in conflict. Underground water has become the main water supply source for large and medium-sized cities in China. The underground water reserve has great influence on natural ecological balance and sustainable development, and has important significance for monitoring underground water.
Due to irregular shape of the earth surface and uneven internal density, the difference exists between the real gravity and the normal gravity. The magnitude of the difference is expressed as a gravity anomaly and the direction is expressed as a deviation of the vertical (DOV). The vertical deviation signal can be decomposed into two parts, namely a high frequency part and a middle and low frequency part, wherein the middle and low frequency part is a long-wave component in the interior of the earth, and the high frequency part is represented as a short-wavelength vertical deviation disturbance quantity generated by surface factors. The vertical deviation is the basic observed quantity of the earth gravity field and contains rich high-frequency information of the gravity field. The vertical deviation can better reflect the real information of the gravity field, and the method has very important application in the fields of resource exploration, geophysical inversion problems, satellite precise orbits, volcanic observation, earthquakes, auxiliary navigation and the like. The high frequency gravity component is important information that is urgently needed in many research fields. Therefore, the method has important significance for acquiring high-resolution and high-precision high-frequency perpendicular deviation information and researching the measurement and approximation method thereof.
The traditional underground water reserve monitoring means is mostly realized by acquiring fixed monitoring network point data of water resources on the earth surface, the method is influenced by the number and distribution of monitoring sites, large-scale and large-scale underground water data cannot be acquired, and the monitoring efficiency is low.
Disclosure of Invention
Based on the above, it is necessary to provide a groundwater reserves monitoring method and system based on vertical deviation disturbance, which solve the problem that large-scale and large-scale groundwater data cannot be obtained, and improve the groundwater reserves monitoring efficiency.
In order to achieve the purpose, the invention provides the following scheme:
a groundwater reserve monitoring method based on vertical deviation disturbance comprises the following steps:
acquiring the running speed of a measuring carrier;
constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; the output of the vertical deviation disturbance two-order random process optimization model is an output result of the two-order random process model after the output passes through a differentiator;
calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-order random process optimization model; the vertical deviation disturbance component comprises a vertical deviation disturbance north-south component and a vertical deviation disturbance east-west component;
and obtaining the underground water reserve variation of the area where the measuring carrier is located by inversion of the vertical deviation disturbance component.
Optionally, the two-step random process optimization model for vertical deviation disturbance is as follows:
Figure BDA0002583144500000021
x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure BDA0002583144500000022
is x1(ii) the first derivative of (t),
Figure BDA0002583144500000023
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000024
in order to be a damping coefficient of the damping,
Figure BDA0002583144500000025
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
Optionally, the calculation formula of the perpendicular deviation disturbance component is
Figure BDA0002583144500000026
Figure BDA0002583144500000027
Xi (t) is the south-north component disturbed by the vertical deviation, eta (t) is the east-west component disturbed by the vertical deviation, and xξ(t) is the intermediate variable in the north-south direction, xη(t) is the intermediate variable in the east-west direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000028
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
Optionally, the obtaining of the groundwater reserve variation of the area where the measurement carrier is located by inversion of the vertical deviation disturbance component specifically includes:
inverting the water reserve variation corresponding to the vertical deviation disturbance component by the vertical deviation disturbance component;
and calculating the underground water reserve variation of the area where the measuring carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation corresponding to the vertical deviation disturbance component.
Optionally, the calculation formula of the groundwater reserve variation is as follows:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
The invention also provides a groundwater reserve monitoring system based on the vertical deviation disturbance, which comprises:
the data acquisition module is used for acquiring the running speed of the measurement carrier;
the model construction module is used for constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; the output of the vertical deviation disturbance two-order random process optimization model is an output result of the two-order random process model after the output passes through a differentiator;
the vertical deviation disturbance calculation module is used for calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-stage random process optimization model; the vertical deviation disturbance component comprises a vertical deviation disturbance north-south component and a vertical deviation disturbance east-west component;
and the inversion module is used for obtaining the underground water reserve variation of the area where the measurement carrier is located by inverting the vertical deviation disturbance component.
Optionally, the two-step random process optimization model for vertical deviation disturbance in the model building module is as follows:
Figure BDA0002583144500000031
x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure BDA0002583144500000032
is x1(ii) the first derivative of (t),
Figure BDA0002583144500000033
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000034
in order to be a damping coefficient of the damping,
Figure BDA0002583144500000035
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
Optionally, the calculation formula of the perpendicular deviation disturbance component in the perpendicular deviation disturbance calculation module is
Figure BDA0002583144500000036
Figure BDA0002583144500000037
Xi (t) is the south-north component disturbed by the vertical deviation, eta (t) is the east-west component disturbed by the vertical deviation, and xξ(t) is the intermediate variable in the north-south direction, xη(t) is the intermediate variable in the east-west direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000041
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
Optionally, the inversion module specifically includes:
the first inversion unit is used for inverting the water reserve variation corresponding to the vertical deviation disturbance component from the vertical deviation disturbance component;
and the calculation unit is used for calculating the underground water reserve variation of the area where the measurement carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation in the soil corresponding to the vertical deviation disturbance component.
Optionally, a calculation formula of the groundwater reserve variation in the calculation unit is as follows:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method and a system for monitoring underground water reserves based on vertical deviation disturbance, which comprises the steps of constructing a vertical deviation disturbance two-order random process optimization model comprising a two-order random process model and a differentiator; and calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-stage random process optimization model, thereby obtaining the underground water reserve variation of the area where the measurement carrier is located through inversion. According to the invention, the output of the random process model passes through a differentiator, so that the gain of a high-frequency disturbance part of the vertical deviation in a low-frequency region can be reduced, and thus, under the action of the differentiator, the high-frequency vertical deviation disturbance has stronger attenuation characteristics in the low-frequency region, the approximation precision of the vertical deviation disturbance is improved, the problem that large-scale and large-scale groundwater data cannot be obtained is solved, and the monitoring efficiency of groundwater reserves is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a groundwater reservoir monitoring method based on vertical deviation disturbance according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a perpendicular line deviation perturbing north and south components according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a vertical deviation perturbing the east-west component according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a groundwater reserve monitoring system based on vertical deviation disturbance according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Excessive exploitation of groundwater causes problems of water depletion, ground settlement, seawater invasion, etc. Most of the traditional means for monitoring the underground water reserves are realized by acquiring fixed monitoring point data of water resources on the earth surface, and the method is influenced by the number and the distribution of monitoring stations. Changes in groundwater reserves can cause changes in local regional mass, and changes in earth mass distribution can result in changes in the earth gravitational field. The vertical deviation disturbance is a gravity field high-frequency component, and the vertical deviation disturbance and the underground water reserve have strong correlation. Thus, groundwater reserves can be inverted from vertical deviation disturbances. The method can monitor the underground water level efficiently, and solves the problem that large-scale and large-scale underground water data cannot be acquired.
The two-step random process model can be written as:
Figure BDA0002583144500000051
the model of high-frequency vertical deviation disturbance and related errors are serious due to the fact that the gain of the power spectral density in a low-frequency region is largeA coupling phenomenon. In order to suppress the coupling effect, so that the power spectral density of the short-wave vertical deviation disturbance model has strong attenuation characteristics in the low-frequency region and reduce the low-frequency gain, the output x (t) of the two-order random process model is passed through a differentiator to obtain the random process x1(t) of (d). This reduces the gain of the high frequency disturbance portion of the vertical deviation in the low frequency region. Under the action of the differentiator, the high-frequency vertical deviation disturbance has stronger attenuation characteristics in a low-frequency region, and the approximation accuracy of the vertical deviation disturbance is improved.
Fig. 1 is a flowchart of a groundwater reserve monitoring method based on vertical deviation disturbance according to an embodiment of the present invention. Referring to fig. 1, the groundwater reserves monitoring method based on vertical deviation disturbance in the present embodiment includes:
step 101: and acquiring the running speed of the measuring carrier. The measuring carrier is a measuring vehicle or a measuring ship.
Step 102: constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator.
And the output of the two-order random process optimization model disturbed by the deviation of the vertical line is the output result of the two-order random process model after the output passes through the differentiator.
Step 103: calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-order random process optimization model; the perpendicular deviation disturbance component comprises a perpendicular deviation disturbance north-south component and a perpendicular deviation disturbance east-west component.
Step 104: and obtaining the underground water reserve variation of the area where the measuring carrier is located by inversion of the vertical deviation disturbance component.
In step 102, the two-step random process model is:
Figure BDA0002583144500000061
the differential equation of the two-order random process of vertical deviation disturbance is as follows:
Figure BDA0002583144500000062
the differential equation of the two-order random process of the deviation disturbance of the vertical line is simplified to obtain:
Figure BDA0002583144500000063
and the simplified differential equation of the two-order random process of the deviation disturbance of the vertical line is the optimization model of the two-order random process of the deviation disturbance of the vertical line. Wherein x (t) is a two-step random process model,
Figure BDA0002583144500000064
is the first derivative of x (t),
Figure BDA0002583144500000065
is the second derivative of x (t), x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure BDA0002583144500000066
is x1(ii) the first derivative of (t),
Figure BDA0002583144500000067
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000068
in order to be a damping coefficient of the damping,
Figure BDA0002583144500000069
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
Figure BDA00025831445000000610
And q (t) may be determined from the travel speed and the measured environmental conditions.
For the convenience of subsequent calculation, the vertical deviation disturbance two-order random process optimization model can be written into a state equation form:
Figure BDA0002583144500000071
in step 103, the calculation formula of the perpendicular deviation disturbance component is
Figure BDA0002583144500000072
Figure BDA0002583144500000073
Xi (t) is a south-north component disturbed by the deviation of the perpendicular line (a component disturbed by the deviation of the perpendicular line on the meridian plane and also called a meridian component disturbed by the deviation of the perpendicular line), eta (t) is an east-west component disturbed by the deviation of the perpendicular line (a component disturbed by the deviation of the perpendicular line on the prime plane and also called a prime component disturbed by the deviation of the perpendicular line), and x (t) is a component disturbed by the deviation of the perpendicular line on theξ(t) is the intermediate variable in the north-south direction, xη(t) is the intermediate variable in the east-west direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000074
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
In step 104, the deviation disturbance component of the perpendicular line contains high-frequency information with abundant space change of the gravity field, and is very sensitive to the mass change of the material on the earth surface. Changes in groundwater reserves will necessarily result in changes in local regional mass and changes in earth mass distribution will result in changes in the earth gravitational field. Thus, groundwater reserves can be inverted from the vertical deviation disturbance component. The change of the mass of the local area can cause the change of the gravity field of the point to be measured, the local area of the earth surface belongs to the high-frequency category of the gravity field, the vertical deviation disturbance component is the high-frequency component of the gravity field, the vertical deviation disturbance component is related to the change of the area mass, and the change quantity of the underground water reserve can be obtained through inversion of the vertical deviation disturbance component. Step 104 specifically includes:
1) and inverting the water reserve variation corresponding to the vertical deviation disturbance component by the vertical deviation disturbance component.
2) And calculating the underground water reserve variation of the area where the measuring carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation corresponding to the vertical deviation disturbance component. The calculation formula of the underground water reserve variation is as follows:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
This embodiment further includes, after step 102: performing Laplace transformation on the two-order random process optimization model of vertical deviation disturbance to obtain a random process x1(t) transfer function and corresponding power spectral density.
x1The transfer function of (t) is:
Figure BDA0002583144500000081
where s represents the complex frequency.
The power spectral density is obtained by transfer function, and the corresponding power spectral density is:
Figure BDA0002583144500000082
where ω denotes frequency, j denotes an imaginary unit,
Figure BDA0002583144500000083
is the variance of q (t).
Two-order random process optimization model x is disturbed by comparing and analyzing output x (t) of two-order random process model and vertical deviation1(t) power spectral density distribution, yielding x1(t) to x: (t) is more strongly attenuated in the low frequency region. Two-order random process optimization model x for vertical deviation disturbance1(t) the gain of the high frequency disturbance portion of the vertical deviation in the low frequency region is reduced. Under the action of the differentiator, the high-frequency vertical deviation disturbance has stronger attenuation characteristics in a low-frequency region, the approaching precision of the vertical deviation is improved, and the problem that large-scale and large-scale groundwater data cannot be acquired is solved, so that the monitoring efficiency of the groundwater reserves is improved.
In order to verify the effectiveness of the underground water reserve monitoring method based on vertical deviation disturbance, the method is adopted to approximate high-frequency disturbance components eta (t) and xi (t) to vertical deviation. As can be seen from fig. 2 and 3, η (t) and ξ (t) fluctuate randomly around 0, and the accuracy of the approximation is within 2 ″, which is high, and therefore, the reliability of the above method of the present embodiment is high. Therefore, the method can effectively measure the vertical deviation high-frequency disturbance quantity, and the accurate vertical deviation high-frequency disturbance quantity can efficiently invert the underground water reserve.
The invention also provides a groundwater reserve monitoring system based on the vertical deviation disturbance, and fig. 4 is a schematic structural diagram of the groundwater reserve monitoring system based on the vertical deviation disturbance provided by the embodiment of the invention. Referring to fig. 4, the groundwater reserves monitoring system based on vertical deviation disturbance includes:
and the data acquisition module 201 is used for acquiring the running speed of the measurement carrier.
The model construction module 202 is used for constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; and the output of the two-order random process optimization model disturbed by the deviation of the vertical line is the output result of the two-order random process model after the output passes through the differentiator.
The perpendicular deviation disturbance calculation module 203 is used for calculating a perpendicular deviation disturbance component based on the perpendicular deviation disturbance two-step random process optimization model; the perpendicular deviation disturbance component comprises a perpendicular deviation disturbance north-south component and a perpendicular deviation disturbance east-west component.
And the inversion module 204 is configured to obtain the amount of change in the underground water reserves of the region where the measurement carrier is located by inverting the vertical deviation disturbance component.
As an optional implementation, the two-step random process optimization model for vertical deviation perturbation in the model building module 202 is:
Figure BDA0002583144500000091
x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure BDA0002583144500000092
is x1(ii) the first derivative of (t),
Figure BDA0002583144500000093
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000094
in order to be a damping coefficient of the damping,
Figure BDA0002583144500000095
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
As an alternative embodiment, the calculation formula of the perpendicular deviation disturbance component in the perpendicular deviation disturbance calculation module 203 is
Figure BDA0002583144500000096
Figure BDA0002583144500000097
Xi (t) is the south-north component disturbed by the vertical deviation, eta (t) is the east-west component disturbed by the vertical deviation, and xξ(t) is the intermediate variable in the north-south direction, xη(t) is east-westIntermediate variable of direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure BDA0002583144500000098
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
As an optional implementation, the inversion module 204 specifically includes:
and the first inversion unit is used for inverting the water reserve variation corresponding to the vertical deviation disturbance component according to the vertical deviation disturbance component.
And the calculation unit is used for calculating the underground water reserve variation of the area where the measurement carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation in the soil corresponding to the vertical deviation disturbance component.
As an alternative embodiment, the calculation formula of the groundwater reserve change amount in the calculation unit is as follows:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
The groundwater reserves monitoring system based on plumb line deviation disturbance that this embodiment provided can reduce the gain of plumb line deviation high frequency disturbance part in the low frequency region, makes high frequency plumb line deviation disturbance have stronger decay characteristic in the low frequency region, improves plumb line deviation disturbance and approaches precision, high-efficient inversion groundwater reserves.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A groundwater reserve monitoring method based on vertical deviation disturbance is characterized by comprising the following steps:
acquiring the running speed of a measuring carrier;
constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; the output of the vertical deviation disturbance two-order random process optimization model is an output result of the two-order random process model after the output passes through a differentiator;
calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-order random process optimization model; the vertical deviation disturbance component comprises a vertical deviation disturbance north-south component and a vertical deviation disturbance east-west component;
and obtaining the underground water reserve variation of the area where the measuring carrier is located by inversion of the vertical deviation disturbance component.
2. A groundwater reserves monitoring method based on vertical deviation disturbance according to claim 1, wherein the two-stage random process optimization model of vertical deviation disturbance is as follows:
Figure FDA0002583144490000011
x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure FDA0002583144490000012
is x1(ii) the first derivative of (t),
Figure FDA0002583144490000013
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure FDA0002583144490000014
in order to be a damping coefficient of the damping,
Figure FDA0002583144490000015
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
3. A groundwater reserve monitoring method based on vertical deviation disturbance according to claim 1, wherein the calculation formula of the vertical deviation disturbance component is
Figure FDA0002583144490000016
Xi (t) is the south-north component disturbed by the vertical deviation, eta (t) is the east-west component disturbed by the vertical deviation, and xξ(t) is the intermediate variable in the north-south direction, xη(t) is the intermediate variable in the east-west direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure FDA0002583144490000018
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0Is a central waveLong.
4. A groundwater reserves monitoring method based on vertical deviation disturbance according to claim 1, wherein the groundwater reserves variation of the area where the measurement carrier is located is obtained by inversion of the vertical deviation disturbance component, and specifically comprises:
inverting the water reserve variation corresponding to the vertical deviation disturbance component by the vertical deviation disturbance component;
and calculating the underground water reserve variation of the area where the measuring carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation corresponding to the vertical deviation disturbance component.
5. A groundwater reserve monitoring method based on vertical deviation disturbance according to claim 4, wherein the calculation formula of the groundwater reserve variation is as follows:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
6. A groundwater reserves monitoring system based on perpendicular deviation disturbance which characterized in that includes:
the data acquisition module is used for acquiring the running speed of the measurement carrier;
the model construction module is used for constructing a vertical deviation disturbance two-order random process optimization model based on the running speed; the vertical deviation disturbance two-order random process optimization model comprises a two-order random process model and a differentiator; the output of the vertical deviation disturbance two-order random process optimization model is an output result of the two-order random process model after the output passes through a differentiator;
the vertical deviation disturbance calculation module is used for calculating a vertical deviation disturbance component based on the vertical deviation disturbance two-stage random process optimization model; the vertical deviation disturbance component comprises a vertical deviation disturbance north-south component and a vertical deviation disturbance east-west component;
and the inversion module is used for obtaining the underground water reserve variation of the area where the measurement carrier is located by inverting the vertical deviation disturbance component.
7. A vertical deviation disturbance-based groundwater reserve monitoring system according to claim 6, wherein the two-stage random process optimization model of the vertical deviation disturbance in the model construction module is:
Figure FDA0002583144490000021
x1(t) is the output of the two-step random process optimization model of vertical deviation disturbance,
Figure FDA0002583144490000022
is x1(ii) the first derivative of (t),
Figure FDA0002583144490000023
is x1Second derivative of (t), ω0Is the center frequency of the frequency band, and is,
Figure FDA0002583144490000024
in order to be a damping coefficient of the damping,
Figure FDA0002583144490000025
is the first derivative of q (t), q (t) is white Gaussian noise, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
8. A plumb-line-deviation-disturbance-based groundwater reserve monitoring system according to claim 6, wherein the calculation formula of the plumb-line deviation disturbance component in the plumb-line deviation disturbance calculation module is
Figure FDA0002583144490000031
Figure FDA0002583144490000032
Xi (t) is the south-north component disturbed by the vertical deviation, eta (t) is the east-west component disturbed by the vertical deviation, and xξ(t) is the intermediate variable in the north-south direction, xη(t) is the intermediate variable in the east-west direction, xξThe derivative of (t) is ξ (t), xηThe derivative of (t) is η (t), qη(t) Process noise in the east-west direction, qξ(t) Process noise in the North-south direction, ω0Is the center frequency of the frequency band, and is,
Figure FDA0002583144490000033
as damping coefficient, ω0=2πV/λ0V is the speed of travel, λ0The center wavelength.
9. A groundwater reserves monitoring system based on vertical deviation disturbance according to claim 6, wherein the inversion module specifically comprises:
the first inversion unit is used for inverting the water reserve variation corresponding to the vertical deviation disturbance component from the vertical deviation disturbance component;
and the calculation unit is used for calculating the underground water reserve variation of the area where the measurement carrier is located according to the water reserve variation, the snow water equivalent variation and the water content variation in the soil corresponding to the vertical deviation disturbance component.
10. A groundwater reserve monitoring system based on vertical deviation disturbance according to claim 9, wherein the calculation formula of the groundwater reserve variation in the calculation unit is:
ΔGN=ΔTNS-ΔSN-ΔSNE;
and delta GN is the variation of underground water reserve, delta TNS is the variation of water reserve corresponding to the deviation disturbance component of the vertical line, delta SN is the variation of equivalent of snow water, and delta SNE is the variation of water content in soil.
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