eEQP-2024:  eEQP-LinkedIn-5-Kamiyama Method 

 

Earthquake Prediction (EQP) Research Based on the TRIZ Philosophy:
(5) Kamiyama Method: Observing Crustal Strains using GNSS Data

      Toru Nakagawa (Emeritus Professor, Osaka Gakuin University)
      Posted:  LinkedIn (TRIZ & Innovation Group), Oct. 3, 2024

Posted here ("TRIZ HP Japan"):  Oct. 7, 2024 ;
           in Japanese  Oct. 7. 2024

Posted:  Oct. 7; Oct. 14, 2024

For going to Japanese pages, press buttons. 

Editor's Note (Toru Nakagawa, Oct. 5, 2024)

Makoto Kamiyama (Professor Emeritus, Tohoku Institute of Technology) et al. presented a paper at the EPSJ (Earthquake Prediction Society of Japan) Conference in Dec. 2023.  They use the precise location data of about 1300 reference points throughout Japan, which are measured and updated daily by the Geospatial Information Authority of Japan using the DNSS satellite. Kamiyama et al. use the triangular FEM mesh to derive the maximum shear strain and the area strain (dilatation) coefficients for each triangular area.   Detailed data and their analysis are reported for Hokkaido Iburi East EQ (Sept. 6, 2018, MJ 6.5).  The dilatation coefficients of four triangle areas around the epicenter are plotted daily against the time axis from 2011 to 2023.  The four areas initially shrank slowly at the same rate, then at the EQ two areas suddenly expanded, and after the EQ all the four areas shrank slowly again as before.  Zooming in to the year 2018, anomalous variations of the dilatation coefficients suddenly appear 3 months before the EQ. Two areas vary positively while two others vary negatively; but, regardless of the direction, the variation patterns are very similar.  The variation started to increase 3 months before the EQ, reached its peak, and slowly decreased in an unstable manner, then changed suddenly at the EQ, and disappeared a few days after the EQ.

Similar abnormal pre-EQ variations were observed in all 3 EQs in the paper. Using these precursors, we can estimate the seismic region and magnitude of the coming EQ on the basis of number and extent of areas showing such abnormal variations. As for the timing of the coming EQ, we learn the cases of 3 years to 3 months, but have not yet found any further indicators of the occurance of EQs. 

The Kamiyama Method is now considered the most useful and promising for Short-term EQ Prediction.  We should observe and analyze many more EQs to refine the method.

 

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Earthquake Prediction (EQP) Research Based on the TRIZ Philosophy:
(5) Kamiyama Method: Observing Crustal Strains using GNSS Data

 

[Click the figure to enlarge further.]    

(Note:  A different fugure was posted here by mistake from Oct. 7 to 14.  Revised on Oct. 14, 2024.)

In part (5), I will introduce you to the Kamiyama Method, a geodetic approach using the GNSS satellite data and considered useful for Short-term EQ Prediction.   Makoto Kamiyama (Professor Emeritus of Tohoku Institute of Technology) and his group in Tohoku IT and Tokai Univ. reported a paper at the EPSJ (Earthquake Prediction Society of Japan) Conference in December 2023.

The GEONET data from the Geospatial Information Authority of Japan (GSI) are used.  The precise locations of about 1,300 control points all over Japan are continuously determined with the GNSS system and published every 30 minutes.  Kamiyama et al. analyze the daily position data of all points using the triangular FEM mesh method (see Fig. (a)).  By selecting 2,152 triangles with sufficient observation data, they converted the daily position data of all points into the maximum shear strain (γmax) and volumetric strain (dilatation) of all triangles.  Note that these strain coefficients represent the averaged values for each triangle area.

They demonstrated their analyses for the top three EQs among the 23 damaging EQs reported by the JMA during 5 years from Jul. 2018 to Jul. 2023.  Here I show the largest case, the Hokkaido Iburi East EQ, which occurred on Sept. 6, 2018 with MJ 6.5.  Its epicenter location is marked with a red star (★) in Fig. (a).  In the enlarged map in Fig. (b), the triangular mesh is shown with the epicenter (★) and the four neighboring triangles A, B, C, D.

Fig. (c) shows the daily plots of the dilatation coefficients of the four triangles (in different colors) for the 12 years from Jul. 2011 to Jul. 2023.   The dilatation coefficient means that the area expands for plus, while the area shrinks for minus.  Thus, we can understand that the areas of four triangles near the epicenter were gradually shrinking more and more before the EQ on Sept. 6, 2018, the areas of two triangles A and C suddenly expanded during the EQ, and then after the EQ, the areas of the four triangles were gradually shrinking again at the same rate as before the EQ.  The general gradual shrinking motion represents the large pressure in the crust, and the sudden expansion motion of the two triangle areas represents the partial rearrangement that occurred during the EQ.

Fig. (d) is the one-year part of Fig. (c) enlarged in the time range from Jan. 2018 to Dec. 2018.  The vertical black line shows the EQ on Sept. 6, 2018.  As can be clearly seen, the dilatation coefficients of the four areas suddenly varied from the gradual (slowly shrinking) trends in mid-May 2018.  The dilatation coefficients of the areas A and B increased (i.e., expanded), while those of C and D decreased (i.e., shrank).  The patterns of variation are more or less similar for the four areas (regardless of their directions); namely, the variation increased slowly, reached the peak, and decreased slowly with seemingly unstable fluctuation.  Then,  on Sept. 6, the EQ occurred, causing areas A and C to expand suddenly.  After the EQ, the four areas shrank gradually at the same rate as before the EQ.

The most remarkable finding in the spatiotemporal data in Figs. (c)  and (d) is the abnormal variations of the dilatation coefficients of the four areas about 3 months before the EQ, as clear precursors of the MJ 6.7 EQ.  Considering such abnormal variations as precursors, we can estimate the seismic area and the size of the impending EQ with the distribution and the size of the affected triangle areas.  The direction of crustal motion of the impending EQ can be estimated from the expansion/shrinkage effects of the abnormal variation in the neighboring triangle areas.

Kamiyama et al. show similar detailed analyses of two other EQs.  In the case of the MJ 5.9 EQ at northwest Chiba on Oct. 7, 2021, the abnormal variations were observed 2.5 years before the EQ with an apparent increase of 3 steps.  In the case of the MJ 6.5 EQ at Noto on May 5, 2023, the abnormal variations were observed 3 years before the EQ with a rapid and then slow increase.  In this way, the precursor abnormal variations appear different in the starting time (from 3 years to 3 months before the EQs) and in their patterns.

In summary, the Kamiyama Method uses the precise location data of many ground points measured by the GNSS satellite system daily or more frequently.  Since the data analysis software has already been developed, the observation system may be deployed further in the world relatively easily.

The observation data are very informative.  First, we should analyze the observation data covering all areas of interest (e.g., the country or the region) to find out the rates of expansion/shrinkage of local areas;  these give us information about the general directions and speed of crustal motion, the regions with large rates or conflicting directions, and the accumulation of strain (for the years from the nearest EQ events in the history of the region), etc.  Such information, together with seismic data in history, tells us about the EQ-risky regions that we should pay special attention to.  Then,  from time to time, we should observe and analyze the data for such risky regions in the manner shown in Figs. (c) and (d) to detect any abnormal variations.  Once some abnormal variations are detected, we should continue to analyze the data of the nearby regions regularly to learn the behavior of the crustal motion.  We would like to get some indicators of impending EQs a few weeks or days before the EQs, but they are not available yet.

Another important issue is to understand the nature of the abnormal variations; they are not co-seismic but pre-seismic, probably related to some slow slip, as suggested by Kamiyama.

In any case, the Kamiyama Method is important in Short-term EQ Prediction. We need to observe and analyze many more cases of EQs.

 

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Last updated on Oct. 14, 2024.     Access point:  Editor: nakagawa@ogu.ac.jp