Earthquake precursor anomaly identification and earthquake short-term and imminent forecasting method based on GNSS displacement information

Abstract

To provide a method relating to the technical field of earthquake short-term and imminent forecasting, and particularly relates to an earthquake precursor anomaly recognition and earthquake short-term and imminent forecasting method based on GNSS displacement information.SOLUTION: The present invention can capture an earthquake deformation precursor more sensitively by using displacement coordination coefficients of measurement stations in different areas, and thereby improve accuracy in an earthquake prediction. An earthquake short-term and imminent forecasting method comprises: constructing absolute deformation field information on a target area; determining a position of an earthquake source according to a position of an abnormal deformation area; further, calculating a change state of a daily displacement coordination coefficient within the abnormal deformation area on the basis of a multi-point displacement coordination coefficient expression, using a displacement sequence of a GNSS measurement station within the abnormal deformation area; and determining a time when the earthquake occurs, using the change state in the displacement coordination coefficient and a quantitative threshold analysis. Accordingly, the present invention realizes a short-term and imminent forecast on a position and time of the earthquake occurrence.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to the technical field of short-term earthquake forecasting, and more particularly to a method for identifying earthquake precursor anomalies and for forecasting imminent earthquakes based on GNSS displacement information. [Background technology]

[0002] Earthquake prediction is an important scientific problem that has not yet been solved, and short-term prediction in particular has become a global challenge. After decades of exploration, earthquake experts around the world have established a system of earthquake seismometry, crustal deformation, electromagnetism, underground fluid science, auxiliary observation, and other disciplines by studying geological structures and crustal movements. During the formation of an earthquake, especially before the occurrence of an earthquake, the area within the earthquake range is subjected to the action of complex stresses inside the rock layers, which causes localization phenomena and the formation of micro-cracks, which causes obvious uneven deformation of the Earth's surface. By using GNSS displacement data, it is possible to realize non-contact observation of the Earth's deformation in all weather conditions. Therefore, it is necessary to use GNSS displacement data to provide a method for identifying earthquake precursor anomalies and short-term prediction of earthquake occurrence, thereby reducing the cost of earthquake forecasting and improving the accuracy of earthquake forecasting. Summary of the Invention [Problem to be solved by the invention]

[0003] In order to solve the above problems, the present invention provides a method for identifying earthquake precursor anomalies and short-term earthquake imminent forecasting based on GNSS displacement information. [Means for solving the problem]

[0004] The method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to the present invention specifically includes the following steps: Step S1: using GNSS precise point positioning technology to process n GNSS measurement stations in a target area, obtain eastward displacement sequences and northward displacement sequences of the n GNSS measurement stations, and use them as an original data source for short-term earthquake imminent forecast; Step S2 of processing the original data source according to the past GNSS displacement information and the generalized common mode error method, eliminating the GNSS measurement station with excessive noise, and determining the predicted data source of the earthquake short-term imminent forecast; Step S3: converting the non-uniformly distributed predicted data source calculation points in the target area into uniformly distributed calculation points based on an interpolation method, and constructing absolute deformation field information of the target area; Step S4: Calculate the absolute deformation field information of the target area every day, and identify the abnormal deformation area in the target area in time scale and space scale according to the maximum absolute deformation value, the minimum absolute deformation value and the average absolute deformation value; Using the displacement sequence of the GNSS measurement stations in the abnormal area, the daily displacement coordination coefficient DCC in the abnormal area is calculated based on the multi-point displacement coordination coefficient calculation formula. i Step S5 of calculating The method includes a step S6 of issuing a short-term imminent forecast of the time and location range of an earthquake when a sudden increase in the displacement coordination coefficient occurs and the value exceeds a threshold value based on the change characteristics and threshold value analysis of the displacement coordination coefficient of the abnormal area.

[0005] Furthermore, the length and width of the target area in step S1 is 300km to 500km.

[0006] Furthermore, in the n GNSS measurement stations in the target area in step S1, the interval between adjacent measurement stations is 10 to 50 km, and the displacement time sequence length of the corresponding GNSS measurement stations is more than two years.

[0007] Furthermore, the daily multi-point displacement coordination coefficient DCC in step S5 i The calculation formula is as follows: JPEG2025031475000002.jpg13170JPEG2025031475000003.jpg16170JPEG2025031475 000004.jpg32170JPEG2025031475000005.jpg16170JPEG2025031475000006.jpg15170

[0008] JPEG2025031475000007.jpg41170

[0009] Furthermore, the threshold analysis in S6 shows that DCC i The threshold range is [0.9±0.2].

[0010] The application of the technical solution of the present invention can achieve the following beneficial effects:

[0011] The present invention proposes a method for identifying earthquake precursor anomalies and predicting earthquakes based on GNSS displacement information, and by using the displacement coordination coefficients of measuring stations in different areas, it can capture the precursors of earthquake deformation more sensitively and improve the accuracy of earthquake prediction. Absolute deformation field information of the target area is constructed, and the epicenter location of the earthquake is determined from the location of the abnormal deformation area. Furthermore, the displacement sequence of the GNSS measuring stations in the abnormal area is used to calculate the daily change situation of the displacement coordination coefficient in the abnormal area based on the multi-point displacement coordination coefficient calculation formula, and the change characteristics of the displacement coordination coefficient and quantitative threshold analysis are used to determine the time of earthquake occurrence, thereby making a short-term imminent forecast of the occurrence time and location range of the earthquake. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing the flow of a method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] As shown in FIG. 1, the method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to the present embodiment includes the following steps: Step S1: using GNSS precise point positioning technology to process n GNSS measurement stations in a target area, obtain eastward displacement sequences and northward displacement sequences of the n GNSS measurement stations, and use them as an original data source for short-term earthquake imminent forecast; Step S2 of processing the original data source according to the past GNSS displacement information and the generalized common mode error method, eliminating the GNSS measurement station with excessive noise, and determining the predicted data source of the earthquake short-term imminent forecast; Step S3: converting the non-uniformly distributed predicted data source calculation points in the target area into uniformly distributed calculation points based on an interpolation method, and constructing absolute deformation field information of the target area; Step S4: Calculate the absolute deformation field information of the target area every day, and identify the abnormal deformation area in the target area in time scale and space scale according to the maximum absolute deformation value, the minimum absolute deformation value and the average absolute deformation value; Using the displacement sequence of the GNSS measurement stations in the abnormal area, the daily displacement coordination coefficient DCC in the abnormal area is calculated based on the multi-point displacement coordination coefficient calculation formula. i Step S5 of calculating The method includes a step S6 of issuing a short-term imminent forecast of the time and location range of an earthquake when a sudden increase in the displacement coordination coefficient occurs and the value exceeds a threshold value based on the change characteristics and threshold value analysis of the displacement coordination coefficient of the abnormal area.

[0014] In step S1 of this embodiment, the existing earthquake and geological data is analyzed, and then a research target area for earthquake forecasting is identified, and the length and width of the area are usually 300km-600km. At the same time, the n GNSS stations in the target area have a distance between adjacent measuring stations of 10-50km. The displacement time sequence length of the corresponding GNSS measuring station is more than 2 years.

[0015] In step S2, based on the existing earthquake, geological information and past GNSS displacement information of the target area, the original displacement is processed using the common mode error method to determine the predicted data source of the earthquake short-term imminent forecast.

[0016] In step S3, based on the predicted data source of the short-term earthquake imminent forecast determined in step S2, the absolute deformation value of the measuring station is calculated using the eastward displacement and northward displacement of the measuring station every day, and then the absolute deformation field information of the target area is constructed by interpolation.

[0017] In step S4, the absolute deformation field information of the target area is analyzed in real time, and the background value of the absolute deformation field is determined when no earthquake occurs. Furthermore, the abnormal deformation area is identified based on the maximum absolute deformation value, the minimum absolute deformation value and the average absolute deformation value of different positions in the target area. The absolute deformation value of the earthquake deformation abnormal area is usually greater than 300%-500% of the absolute deformation field background value.

[0018] In step S5, the daily multi-point displacement coordination coefficient DCC i The calculation formula for this is as follows: JPEG2025031475000008.jpg13170JPEG2025031475000009.jpg16170JPEG2025031475 000010.jpg32170JPEG2025031475000011.jpg16170JPEG2025031475000012.jpg15170

[0019] JPEG2025031475000013.jpg41170

[0020] Obtain the daily change status of multi-point displacement coordination coefficients in the abnormal area.

[0021] In step S6, the daily multi-point displacement coordination coefficients in the anomalous area are observed and analyzed in real time. When the deformation in the anomalous area is not significant, the displacement coordination coefficient changes to vary smoothly with a small range, and the displacement coordination coefficient value is usually between 0.01 and 0.3. When an earthquake is imminent and the deformation in the anomalous area is significant, the displacement coordination coefficient increases sharply. According to statistical calculations of a large number of earthquake cases, the precursor threshold before the occurrence of an earthquake is [0.9±0.2]. Using GNSS information, the displacement changes of the measurement stations are observed in real time, and when a sudden increase occurs in the displacement coordination coefficient of the measurement station and the threshold is exceeded, a short-term earthquake imminent prediction is made.

[0022] The present invention is a method for identifying earthquake precursor anomalies and predicting earthquakes based on GNSS displacement information, and by using the displacement coordination coefficients of measurement stations in different areas, it is possible to more sensitively capture the precursors of earthquake deformation and improve the accuracy of earthquake prediction. Absolute deformation field information is constructed, and the epicenter location of the earthquake is determined from the location of the abnormal deformation area, and further, the displacement sequence of the GNSS measurement stations in the abnormal area is used to calculate the daily change situation of the displacement coordination coefficient in the abnormal area based on the multi-point displacement coordination coefficient calculation formula, and the change characteristics of the displacement coordination coefficient and quantitative threshold analysis are used to realize short-term imminent forecast of earthquakes.

Claims

1. A method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information, comprising: Step S1: using GNSS precise point positioning technology to process n GNSS measurement stations in a target area, obtain eastward displacement sequences and northward displacement sequences of the n GNSS measurement stations, and use them as an original data source for short-term earthquake imminent forecast; Step S2 of processing the original data source according to the past GNSS displacement information and the generalized common mode error method, eliminating the GNSS measurement station with excessive noise, and determining the predicted data source of the earthquake short-term imminent forecast; Step S3: converting the non-uniformly distributed predicted data source calculation points in the target area into uniformly distributed calculation points based on an interpolation method, and constructing absolute deformation field information of the target area; S4: calculating absolute deformation field information of the target area every day, and identifying abnormal deformation areas in the target area in time scale and space scale according to the maximum absolute deformation value, the minimum absolute deformation value and the average absolute deformation value; Using the displacement sequence of the GNSS measurement station in the abnormal area, the daily displacement coordination coefficient DCC in the abnormal area is calculated based on the multi-point displacement coordination coefficient calculation formula. ｉ Step S5 of calculating Step S6: based on the change characteristics and threshold analysis of the displacement coordination coefficient of the abnormal area, when a sudden increase in the displacement coordination coefficient occurs and the value exceeds a threshold, a short-term imminent forecast is made for the time and location of the earthquake; A method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information, comprising:

2. The length and width of the target area in step S1 is 300km to 500km.

2. The method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to claim 1.

3. In the step S1, the n GNSS measurement stations in the target area have an interval between adjacent measurement stations of 10 to 50 km, and the displacement time sequence length of the corresponding GNSS measurement stations is 2 years or more.

2. The method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to claim 1.

4. The daily multi-point displacement coordination coefficient DCC in step S5 ｉ The formula is: and 2. The method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to claim 1.

5. The threshold quantitative analysis in S6 is carried out for different types of earthquakes. ｉ The threshold range is [0.9±0.2] 2. The method for identifying earthquake precursor anomalies and for short-term earthquake forecasting based on GNSS displacement information according to claim 1.

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