Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic Tomography Including NIED MOWLAS Hi-net and S-net Data

*Makoto Matsubara, Hiroshi Sato, Kenji Uehira, Masashi Mochizuki, Toshihiko Kanazawa, Narumi Takahashi, Kensuke Suzuki and Shin'ichiro Kamiya*

#### **Abstract**

Japanese Islands are composed of four plates, with two oceanic plates subducting beneath the two continental plates. In 2016 the National Research Institute for Earth Science and Disaster Resilience (NIED) Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net) started seismic observation of the offshore Hokkaido to Boso region in the Pacific Ocean, and Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) was transferred to NIED. We add the NIED S-net and DONET datasets to NIED highsensitivity seismograph network (Hi-net) and full range seismograph network (F-net) datasets used in the previous study and obtain the three-dimensional seismic velocity structure beneath the Pacific Ocean as well as Japanese Islands. NIED S-net data dramatically improve the resolution beneath the Pacific Ocean at depths of 10–20 km because the seismic stations are located above the earthquakes and on the east side of the Japan Trench. We find a NS high-Vp zone at depths of 20–30 km. The 2018 Eastern Iburi earthquake occurred below the northern part of this high-V zone. The coseismic slip plane of the 2011 Tohokuoki earthquake has low Vp/Vs, but its large slip region has high Vp. The broad low-Vp/Vs region may play a role in large earthquake occurrence.

**Keywords:** seismic tomography, failed rift, offshore event, NIED S-net, DONET, NIED Hi-net

#### **1. Introduction**

The Japanese Islands are mainly composed of the Eurasian (EUR) and the North American (NA) plates, and a number of small islands are on the Philippine Sea (PHS) and the Pacific (PAC) plates (**Figure 1**). The PHS and PAC oceanic plates are subducting beneath the EUR and the NA plates. A number of earthquakes occurred both at the plate interfaces and within the plates.

#### **Figure 1.** *Name of plates and location.*

After the Kobe earthquake in January 1995, the Japanese government enacted the Special Measure Law on Earthquake Disaster Prevention in July 1995. This was to promote a comprehensive national policy on earthquake disaster prevention. Based on this goal, the National Research Institute for Earth Science and Disaster Resilience (NIED) contracted the deployment of the nationwide high-sensitivity seismograph network (Hi-net) [1] since NIED had already accumulated the experience for the Tokyo metropolitan deep borehole array and operated the Kanto-Tokai seismic network since 1979. NIED operates the Hi-net with approximately 800 stations since 2000 [2] and the full range seismograph network (F-net) [3] with approximately 70 stations composed of broadband seismographs since 1994 [4]. The Japan Meteorological Agency (JMA), the national universities, and other institutes operate other seismic networks with a total of approximately 600 stations for the detection of microseismicity. NIED operates ocean-bottom seismic stations beneath the Sagami Bay, while the JMA operates offshore the Tokai and Boso regions. The Earthquake Research Institute, University of Tokyo, operates the network offshore Sanriku, and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) operates offshore Kushiro and Muroto networks. JAMSTEC started the construction of the Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) [5] off Kii and Muroto Peninsulas near the Nankai Trough in 2010, and they started operation networks offshore Kii (in 2014) and Muroto (in 2016) Peninsulas. NIED deployed the Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net) [6] after the 2011 offshore Tohoku Earthquake (the Tohoku-oki event), which began operating in 2016 [7, 8]. DONET was transferred to NIED from April 2016. NIED started the operation of Monitoring of Waves on Land and Seafloor (MOWLAS) composed of Hi-net, F-net, S-net, DONET, strong-motion seismograph networks (K-NET and KiK-net) [9], and Volcano Observation Network (V-net) [10].

**73**

**Figure 2.**

*S-net in (b).*

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

NIED S-net and DONET teams manually pick the arrival time data at the oceanic seismic stations after NIED Hi-net team has determined the hypocenters using the land stations. We confirm the difference of shallow hypocenters between the determination by only NIED Hi-net and that by NIED Hi-net and NIED S-net. Stars in **Figure 2** show the hypocenters at depths shallower than 20 km beneath the PAC plate determined by NIED Hi-net from September 11, 2017, to the end of 2018. The shallow hypocenters near the main island tend to remain shallow; however, hypocenters more than 200 km off the coast shifted significantly deeper to 40–80 km depth when including the S-net arrival time data (**Figure 2**). Deep events determined by NIED Hi-net on the east side of a longitude of 144°E are also shifted shallower. This suggests that it is important to include the S-net data for reliable

Three-dimensional (3D) seismic velocity structure beneath the whole Japanese Islands has been studied using the vast data of seismic stations within the Japanese Islands maintained by NIED, JMA, national universities, and the other national and local governmental institutes (e.g., [11–14]). These studies used data obtained mainly at land-based seismic stations with a very few seismic stations on the sea floor such as Sagami Bay, off Kushiro, Sanriku, Boso, and Tokai regions. Reference [14] investigated the structure beneath the PAC plate at depths of 30–50 km using events that occurred under the Pacific Ocean (PO) with focal depths determined by NIED F-net. However, that study was not able to clarify the shallow structure beneath the PO at depths of 0–20 km because of the lack of seismic stations on the seafloor of the PO. The seismic ray takeoff angles proceed downward from the events to the seismic stations on land, and they do not pass through the shallow zone beneath the ocean since the distance from the hypocenter to the seismic stations is usually over 150 km. We investigated the 3D seismic velocity structure of and around Japanese Islands including the Sea of Japan and PO by the seismic tomographic method. We added the arrival time data detected in the S-net, the DONET, and the Hi-net datasets, operated by NIED, as well as other datasets, operated by multiple organizations, after 2016 in addition to the data used in [14]. Then

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

hypocenter locations of offshore events.

we applied the seismic tomography to these datasets.

*Comparison of hypocenters determined by the NIED (a) Hi-net and (b) Hi-net and S-net. Stars denote hypocenters determined at depths shallower than 20 km by only Hi-net in (a) and redetermined by Hi-net and*  *Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

NIED S-net and DONET teams manually pick the arrival time data at the oceanic seismic stations after NIED Hi-net team has determined the hypocenters using the land stations. We confirm the difference of shallow hypocenters between the determination by only NIED Hi-net and that by NIED Hi-net and NIED S-net. Stars in **Figure 2** show the hypocenters at depths shallower than 20 km beneath the PAC plate determined by NIED Hi-net from September 11, 2017, to the end of 2018. The shallow hypocenters near the main island tend to remain shallow; however, hypocenters more than 200 km off the coast shifted significantly deeper to 40–80 km depth when including the S-net arrival time data (**Figure 2**). Deep events determined by NIED Hi-net on the east side of a longitude of 144°E are also shifted shallower. This suggests that it is important to include the S-net data for reliable hypocenter locations of offshore events.

Three-dimensional (3D) seismic velocity structure beneath the whole Japanese Islands has been studied using the vast data of seismic stations within the Japanese Islands maintained by NIED, JMA, national universities, and the other national and local governmental institutes (e.g., [11–14]). These studies used data obtained mainly at land-based seismic stations with a very few seismic stations on the sea floor such as Sagami Bay, off Kushiro, Sanriku, Boso, and Tokai regions. Reference [14] investigated the structure beneath the PAC plate at depths of 30–50 km using events that occurred under the Pacific Ocean (PO) with focal depths determined by NIED F-net. However, that study was not able to clarify the shallow structure beneath the PO at depths of 0–20 km because of the lack of seismic stations on the seafloor of the PO. The seismic ray takeoff angles proceed downward from the events to the seismic stations on land, and they do not pass through the shallow zone beneath the ocean since the distance from the hypocenter to the seismic stations is usually over 150 km. We investigated the 3D seismic velocity structure of and around Japanese Islands including the Sea of Japan and PO by the seismic tomographic method. We added the arrival time data detected in the S-net, the DONET, and the Hi-net datasets, operated by NIED, as well as other datasets, operated by multiple organizations, after 2016 in addition to the data used in [14]. Then we applied the seismic tomography to these datasets.

**Figure 2.**

*Comparison of hypocenters determined by the NIED (a) Hi-net and (b) Hi-net and S-net. Stars denote hypocenters determined at depths shallower than 20 km by only Hi-net in (a) and redetermined by Hi-net and S-net in (b).*

*Seismic Waves - Probing Earth System*

After the Kobe earthquake in January 1995, the Japanese government enacted the Special Measure Law on Earthquake Disaster Prevention in July 1995. This was to promote a comprehensive national policy on earthquake disaster prevention. Based on this goal, the National Research Institute for Earth Science and Disaster Resilience (NIED) contracted the deployment of the nationwide high-sensitivity seismograph network (Hi-net) [1] since NIED had already accumulated the experience for the Tokyo metropolitan deep borehole array and operated the Kanto-Tokai seismic network since 1979. NIED operates the Hi-net with approximately 800 stations since 2000 [2] and the full range seismograph network (F-net) [3] with approximately 70 stations composed of broadband seismographs since 1994 [4]. The Japan Meteorological Agency (JMA), the national universities, and other institutes operate other seismic networks with a total of approximately 600 stations for the detection of microseismicity. NIED operates ocean-bottom seismic stations beneath the Sagami Bay, while the JMA operates offshore the Tokai and Boso regions. The Earthquake Research Institute, University of Tokyo, operates the network offshore Sanriku, and the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) operates offshore Kushiro and Muroto networks. JAMSTEC started the construction of the Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) [5] off Kii and Muroto Peninsulas near the Nankai Trough in 2010, and they started operation networks offshore Kii (in 2014) and Muroto (in 2016) Peninsulas. NIED deployed the Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net) [6] after the 2011 offshore Tohoku Earthquake (the Tohoku-oki event), which began operating in 2016 [7, 8]. DONET was transferred to NIED from April 2016. NIED started the operation of Monitoring of Waves on Land and Seafloor (MOWLAS) composed of Hi-net, F-net, S-net, DONET, strong-motion seismograph networks (K-NET and KiK-net) [9], and Volcano Observation Network (V-net) [10].

**72**

**Figure 1.**

*Name of plates and location.*

#### **2. Data and method**

The target region, 20–48°N and 120–148°E, covers the whole Japanese Islands from Hokkaido to Okinawa and the seismic stations both Hi-net on land and S-net and DONET beneath the ocean. In addition to the arrival time data used by [14], 1,782,425 P- and 1,528,733 S-wave arrival times from 32,952 earthquakes recorded at approximately 2000 stations including NIED S-net and DONET from April 2016 to June 2018 were selected. A total of 7,853,757 P-wave arrival data and 4,604,780 S-wave arrival data from 112,631 events are available after merging the new datasets (**Figure 3**).

We used the seismic tomographic method [15, 16] with spatial velocity correlation and station corrections to the original code by [11]. Grid nodes were placed with half of the spatial resolution. We performed smoothing in order to stabilize the solution for the inverse problem with the LSQR algorithm [17] since arbitrary damping matrix with combination of diagonal and smoothing matrices could be assumed.

We placed 3D grid nodes to construct the velocity (slowness) structure with the grid spacing shown in **Table 1** and adopted the 1D structure used in the routine determination of hypocenters at the Hi-net and S-net [18] as the initial velocity model (**Figure 4**). No velocity discontinuities such as Moho discontinuities or the plate boundary between the EUR and PAC or PHS plates were assumed in this study. This is because there were enough data to estimate the steep velocity gradient to represent plate boundaries so that velocity discontinues in the model were not necessary [13, 16, 19]. The total number of unknowns, 4,417,505, for P-wave slowness is the same as those for S-wave slowness. We solved the P- and S-wave slowness at each grid node from more than 10 associated rays.

First, we inverted the P- and S-wave seismic velocities using the initial hypocenter location. Second, both hypocenters and 3D seismic velocity structure were inverted simultaneously. We included the arrival times from the events beneath the ocean before 2015 in addition to the data used by [14]. Focal depths of offshore events were determined by NIED F-net or [20] since offshore events determined by only NIED Hi-net are not reliable. For these offshore events, only epicenters are inverted by the 3D seismic velocity structure, while hypocenter depths are fixed.

**75**

during the inversion.

**Figure 4.**

**Table 1.**

*Grid interval and resolution size.*

from 0.812 to 0.239 s after 11 iterations.

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

**Depth Grid interval Resolution/checkerboard pattern**

0–10 0.1° 2.5 0.2° 5 10–40 5 10 40–60 10 20 60–180 15 30 180–300 20 40 300− 25 50

**Horizontal Vertical (km) Horizontal Vertical (km)**

We do not fix any condition for the events after 2016 detected by NIED S-net and DONET and the events within 50 km of the onshore seismic networks before 2015

*Seismic velocity structures of the initial model and the average of the final 3D model.*

Residuals are improved to within 0.5 s for P-wave and 0.6 s for S-wave in the travel time inversion. In the final iteration, we used 6,356,481 P-wave arrival data and 3,534,482 S-wave arrival data to solve for the P-wave slowness at 1,135,165 grid nodes and the S-wave slowness at 1,103,525 grid nodes. The inversion reduces RMS of the P-wave travel time residual from 0.561 to 0.192 s and that of the S-wave data

We conducted a checkerboard resolution test to evaluate the reliability of our solution [21]. We assumed a ± 5% checkerboard pattern and calculated synthetic travel times with random noise of 0 mean and standard deviations of 0.13 and 0.24 s for P- and S-waves, respectively. The standard deviations for random noise were derived from the average of the estimated uncertainty of the manually picked arrival times. The weight of data is inversely proportional to each width of picking error. The damping factors for the P-wave inversion are twice those for the S-wave inversion, since the average standard deviation of P-wave picking errors is almost half of that of S-wave.

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

**Figure 3.** *Distribution of hypocenters and seismic stations used for seismic tomography.*


*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

#### **Table 1.**

*Seismic Waves - Probing Earth System*

at each grid node from more than 10 associated rays.

*Distribution of hypocenters and seismic stations used for seismic tomography.*

The target region, 20–48°N and 120–148°E, covers the whole Japanese Islands from Hokkaido to Okinawa and the seismic stations both Hi-net on land and S-net and DONET beneath the ocean. In addition to the arrival time data used by [14], 1,782,425 P- and 1,528,733 S-wave arrival times from 32,952 earthquakes recorded at approximately 2000 stations including NIED S-net and DONET from April 2016 to June 2018 were selected. A total of 7,853,757 P-wave arrival data and 4,604,780 S-wave arrival data from 112,631 events are available after merging the new datasets (**Figure 3**). We used the seismic tomographic method [15, 16] with spatial velocity correlation and station corrections to the original code by [11]. Grid nodes were placed with half of the spatial resolution. We performed smoothing in order to stabilize the solution for the inverse problem with the LSQR algorithm [17] since arbitrary damping matrix with combination of diagonal and smoothing matrices could be assumed. We placed 3D grid nodes to construct the velocity (slowness) structure with the grid spacing shown in **Table 1** and adopted the 1D structure used in the routine determination of hypocenters at the Hi-net and S-net [18] as the initial velocity model (**Figure 4**). No velocity discontinuities such as Moho discontinuities or the plate boundary between the EUR and PAC or PHS plates were assumed in this study. This is because there were enough data to estimate the steep velocity gradient to represent plate boundaries so that velocity discontinues in the model were not necessary [13, 16, 19]. The total number of unknowns, 4,417,505, for P-wave slowness is the same as those for S-wave slowness. We solved the P- and S-wave slowness

First, we inverted the P- and S-wave seismic velocities using the initial hypocenter location. Second, both hypocenters and 3D seismic velocity structure were inverted simultaneously. We included the arrival times from the events beneath the ocean before 2015 in addition to the data used by [14]. Focal depths of offshore events were determined by NIED F-net or [20] since offshore events determined by only NIED Hi-net are not reliable. For these offshore events, only epicenters are inverted by the 3D seismic velocity structure, while hypocenter depths are fixed.

**2. Data and method**

**74**

**Figure 3.**

*Grid interval and resolution size.*

#### **Figure 4.**

*Seismic velocity structures of the initial model and the average of the final 3D model.*

We do not fix any condition for the events after 2016 detected by NIED S-net and DONET and the events within 50 km of the onshore seismic networks before 2015 during the inversion.

Residuals are improved to within 0.5 s for P-wave and 0.6 s for S-wave in the travel time inversion. In the final iteration, we used 6,356,481 P-wave arrival data and 3,534,482 S-wave arrival data to solve for the P-wave slowness at 1,135,165 grid nodes and the S-wave slowness at 1,103,525 grid nodes. The inversion reduces RMS of the P-wave travel time residual from 0.561 to 0.192 s and that of the S-wave data from 0.812 to 0.239 s after 11 iterations.

We conducted a checkerboard resolution test to evaluate the reliability of our solution [21]. We assumed a ± 5% checkerboard pattern and calculated synthetic travel times with random noise of 0 mean and standard deviations of 0.13 and 0.24 s for P- and S-waves, respectively. The standard deviations for random noise were derived from the average of the estimated uncertainty of the manually picked arrival times. The weight of data is inversely proportional to each width of picking error. The damping factors for the P-wave inversion are twice those for the S-wave inversion, since the average standard deviation of P-wave picking errors is almost half of that of S-wave.

### **3. Results**

#### **3.1 Results of checkerboard resolution test**

**Figure 5** shows the results of checkerboard resolution test. We calculate the recovery rate and stability with surrounding grid nodes in order to confirm wellresolved area [15]. The resolutions of Vp and Vs at depths of 5–30 km beneath main four islands are good. At depths of 40–60 km, resolutions are not good along the Sea of Japan coast because there are few deep earthquakes that can be used for inversion.

**77**

**Figure 6.**

*depths of 10 and 20 km denote the median tectonic line.*

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

NIED S-net data increase the resolution at depths of 10–60 km from Honshu to the Japan Trench (**Figure 5**). Reference [14] used the offshore events such as aftershocks of the Tohoku-oki earthquake. The presence of a seismic station above the events is extremely important for the estimation of velocity structure as well as the determination of hypocenters. The resolutions at depths of 0 and 5 km are still not good in spite of the use of S-net data because the incident angle to the S-net stations are mainly steep and ray paths do not run horizontally because of the lack of shallow earthquakes. Resolutions near the triple junction of Japan Trench and Sagami Trough where three plates, PAC, PHS, and EUR, meet are good at depths of

Beneath the DONET area, the resolution at depths of 10–60 km is good for Vp, and those at depths of 5–40 km are good for Vs. The resolved zone extends to the

We calculated the average 1D model from the final 3D velocity structure (**Figure 4**).

At a depth of 5 km, low-Vp and low-Vs regions are located along the PAC coast beneath southeastern Hokkaido, northeastern Honshu, most of Kanto, Sagami Bay, southern Kinki, and southern Shikoku regions. A low-Vs region extends beneath the entire Shikoku and southern Chugoku regions. A low-Vp/Vs region runs along the Ou backbone range in northeastern Japan and central Japan. Other regions have high Vp/Vs. At a depth of 10 km, low-Vp regions extend beneath the active volcanoes in the northeastern and central Honshu and Kyushu regions. Low-Vs regions are almost the same as those at a depth of 5 km. High-Vp/Vs regions are distributed at central Hokkaido and coastal area in northeastern Japan. Low-Vp/Vs covers the other regions. At a depth of 20 km, low-Vp regions lie beneath volcanoes in Hokkaido, central Honshu, and Kyushu. Low-Vs regions extend beneath the volcanoes and back-arc side of Honshu. Both low-Vp and low-Vs regions extend from central Kinki to

*Map views of Vp and Vs perturbation and Vp/Vs. Colored area is the resolved area. Broken white lines at* 

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

20–30 km. This is an advantage of using NIED S-net.

**3.2 Map views at depths**

Nankai Trough since there is sufficient seismicity in this area.

We also showed the perturbation from these average velocities (**Figure 6**).

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

NIED S-net data increase the resolution at depths of 10–60 km from Honshu to the Japan Trench (**Figure 5**). Reference [14] used the offshore events such as aftershocks of the Tohoku-oki earthquake. The presence of a seismic station above the events is extremely important for the estimation of velocity structure as well as the determination of hypocenters. The resolutions at depths of 0 and 5 km are still not good in spite of the use of S-net data because the incident angle to the S-net stations are mainly steep and ray paths do not run horizontally because of the lack of shallow earthquakes. Resolutions near the triple junction of Japan Trench and Sagami Trough where three plates, PAC, PHS, and EUR, meet are good at depths of 20–30 km. This is an advantage of using NIED S-net.

Beneath the DONET area, the resolution at depths of 10–60 km is good for Vp, and those at depths of 5–40 km are good for Vs. The resolved zone extends to the Nankai Trough since there is sufficient seismicity in this area.

#### **3.2 Map views at depths**

*Seismic Waves - Probing Earth System*

**3.1 Results of checkerboard resolution test**

**Figure 5** shows the results of checkerboard resolution test. We calculate the recovery rate and stability with surrounding grid nodes in order to confirm wellresolved area [15]. The resolutions of Vp and Vs at depths of 5–30 km beneath main four islands are good. At depths of 40–60 km, resolutions are not good along the Sea of Japan coast because there are few deep earthquakes that can be

**3. Results**

used for inversion.

**76**

**Figure 5.**

*Map views of checkerboard resolution test for Vp and Vs. green line surrounds the well-resolved area.*

We calculated the average 1D model from the final 3D velocity structure (**Figure 4**). We also showed the perturbation from these average velocities (**Figure 6**).

At a depth of 5 km, low-Vp and low-Vs regions are located along the PAC coast beneath southeastern Hokkaido, northeastern Honshu, most of Kanto, Sagami Bay, southern Kinki, and southern Shikoku regions. A low-Vs region extends beneath the entire Shikoku and southern Chugoku regions. A low-Vp/Vs region runs along the Ou backbone range in northeastern Japan and central Japan. Other regions have high Vp/Vs.

At a depth of 10 km, low-Vp regions extend beneath the active volcanoes in the northeastern and central Honshu and Kyushu regions. Low-Vs regions are almost the same as those at a depth of 5 km. High-Vp/Vs regions are distributed at central Hokkaido and coastal area in northeastern Japan. Low-Vp/Vs covers the other regions.

At a depth of 20 km, low-Vp regions lie beneath volcanoes in Hokkaido, central Honshu, and Kyushu. Low-Vs regions extend beneath the volcanoes and back-arc side of Honshu. Both low-Vp and low-Vs regions extend from central Kinki to

#### **Figure 6.**

*Map views of Vp and Vs perturbation and Vp/Vs. Colored area is the resolved area. Broken white lines at depths of 10 and 20 km denote the median tectonic line.*

Kyushu region across central Shikoku. This low-V zone remains the same as at a depth of 5 km. High-Vp/Vs regions cover the Ou backbone range and back-arc side of northeastern Honshu.

At a depth of 30 km, low-Vp extends beneath the northeastern Honshu, central and southwestern Honshu, and northern Kyushu regions. Low-Vs regions extend beneath most of Honshu, Kyushu, and northern Shikoku regions. High-Vp/Vs regions cover almost all Japanese Islands except the central Hokkaido.

At a depth of 40 km, low-Vp regions exist beneath the volcanoes in southeastern Hokkaido and northeastern and central Honshu regions. The low-Vp regions beneath the volcanoes in the northeastern Japan extend to back-arc side. Low-Vs regions are clarified beneath the volcanoes in southeastern Hokkaido and central Honshu regions. Low-Vs regions beneath the northeastern Honshu can be found east of the volcanic front as are low-Vp regions. Low-Vp/Vs regions cover the central mountains across Hokkaido and northeastern and central Honshu.

At a depth of 60 km, low-Vp and low-Vs regions extend beneath the volcanoes in Honshu and central Honshu. High-Vp and Vs regions extend beneath the Kinki, Shikoku, and eastern Kyushu regions where the PHS plates subduct. High-Vp/Vs regions are distributed across western Hokkaido, central Honshu, and central Shikoku regions.

At a depth of 90 km, low-Vp and low-Vs regions exist beneath the volcanoes beneath Hokkaido and Honshu. High-Vp and Vs regions extend to the east of northeastern Japan where the PAC plate subducts. High-Vp/Vs regions cover northern and southwestern Hokkaido, central Honshu, and central Kyushu regions.

#### **3.3 Velocity structure beneath the Pacific Ocean off northeastern Japan beneath the S-net**

At a depth of 10 km, a low-Vp and low-Vs zone extends along the coast of the PO in the northeastern Honshu. A high-Vp and high-Vs zone exists between the longitudes of 142 and 143°. East of longitude of 143° (**Figure 6A** and **B**), low-Vp, and low-Vs zone shows again. Vp/Vs is generally low except in some small regions.

At a depth of 20 km, a high-Vp and high-Vs zone extends along the coast of the PO in the northeastern Honshu, in contrast to the structure at a depth of 10 km. Low-V zones extend to the east of the high-Vp zone; however, some high-Vp zones exist among the low-Vp zones (**Figure 6C**). High-Vs zones are mixed with minor low-Vs zone off the east of northeastern Honshu, extending to a longitude of 143.5° (**Figure 6D**). This pattern can be seen with Vp at a depth of 10 km. Vp/Vs is also broadly low, and this pattern of Vp/Vs can be seen when the depth is 10 km except in some regions.

At a depth of 30 km, low-Vp zone extends off the east of northeastern Honshu between longitudes of 142 and 143.5 and to the region off the southeast of Hokkaido. High-Vp zone can be seen along the Japan Trench. Two patches of low-Vs zones exist in the east of northeastern Honshu at latitude of 37–40° and longitude of 142–143° and at latitude of 35–36° and longitude of 141–142°. High-Vp/Vs region is bounded by the low-Vp/Vs region, a north–south "stripe" pattern.

At a depth of 40 km, low-Vp and low-Vs zones extend between longitude of 142–143° and latitudes of 37–41°. These low-Vp and low-Vs zones extend to the west of the Hidaka Mountains. High-Vp and high-Vs zones can be seen on the east of the low-V zone and reach the east of the Japan Trench. Vp/Vs in this area is moderate except for some low-Vp/Vs regions with north–south trend.

At a depth of 60 km, low-Vp and low-Vs zones extend just off the coast of the PAC in the northeastern Honshu. High-Vp and high-Vs zones extend broadly on the east of the narrow low-V zone. Vp/Vs in this area is high.

**79**

**Figure 7.**

*Station corrections for (a) Vp and (b) Vs.*

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

**3.4 Velocity structure beneath the Pacific Ocean off Kii and Muroto peninsula** 

At depths of 20 and 30 km, low-Vp zones extend around the hypocenters of the large events with magnitude 6.9 and 7.4 that occurred on September 5, 2004. Low-Vs zones partly exist within the low-Vp zone. We cannot resolve the continuous structure from Honshu at depths of 5–10 km since the number of events for seismic tomography beneath the DONET stations is small. This is because the DONET picked data are basically added after the Hi-net manual picking. The seismic tomography will be recalculated when the microearthquake data triggered at DONET stations become available.

The station corrections for the final model are shown in **Figure 7**. Red stations denote positive O-C travel times. It means that the modeled velocity is too high due to thick sediment or low-V materials since the calculated travel time is too small. It also depends on the depth of borehole of Hi-net stations. The seismometers of the Hi-net stations are typically deployed at depths of around 100–200 m, and low-Vp sediment materials are estimated beneath the backbone range and back-arc side of Japan. Large station corrections are estimated along the Sea of Japan coast in northeastern Honshu since there are thick sediments, while borehole stations are relatively shallow. For Vs, there are many blue-colored stations meaning that the velocity model is too slow. Large station corrections are also estimated on the Sea of Japan side of northeastern Honshu. For S-net stations, blue stations can be seen near the coast and the Japan Trench. Red stations are shown between them for both Vp and Vs. It suggests that the seismic velocity model is too slow near the coast and the Japan Trench and too fast between them. For DONET stations, red stations are shown near the coast and blue stations reside

off the coast. It means that the modeled seismic velocity is too high near the coast.

**Figure 8** shows the histogram of the epicentral movement during the iterations. Epicenters determined by NIED F-net and [20] are shifted over 50 km

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

**beneath the DONET**

**3.5 Station corrections**

**3.6 Movement of hypocenters**

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

#### **3.4 Velocity structure beneath the Pacific Ocean off Kii and Muroto peninsula beneath the DONET**

At depths of 20 and 30 km, low-Vp zones extend around the hypocenters of the large events with magnitude 6.9 and 7.4 that occurred on September 5, 2004. Low-Vs zones partly exist within the low-Vp zone. We cannot resolve the continuous structure from Honshu at depths of 5–10 km since the number of events for seismic tomography beneath the DONET stations is small. This is because the DONET picked data are basically added after the Hi-net manual picking. The seismic tomography will be recalculated when the microearthquake data triggered at DONET stations become available.

#### **3.5 Station corrections**

*Seismic Waves - Probing Earth System*

of northeastern Honshu.

and central Shikoku regions.

**the S-net**

in some regions.

Kyushu region across central Shikoku. This low-V zone remains the same as at a depth of 5 km. High-Vp/Vs regions cover the Ou backbone range and back-arc side

regions cover almost all Japanese Islands except the central Hokkaido.

mountains across Hokkaido and northeastern and central Honshu.

southwestern Hokkaido, central Honshu, and central Kyushu regions.

At a depth of 30 km, low-Vp extends beneath the northeastern Honshu, central and southwestern Honshu, and northern Kyushu regions. Low-Vs regions extend beneath most of Honshu, Kyushu, and northern Shikoku regions. High-Vp/Vs

At a depth of 40 km, low-Vp regions exist beneath the volcanoes in southeastern Hokkaido and northeastern and central Honshu regions. The low-Vp regions beneath the volcanoes in the northeastern Japan extend to back-arc side. Low-Vs regions are clarified beneath the volcanoes in southeastern Hokkaido and central Honshu regions. Low-Vs regions beneath the northeastern Honshu can be found east of the volcanic front as are low-Vp regions. Low-Vp/Vs regions cover the central

At a depth of 60 km, low-Vp and low-Vs regions extend beneath the volcanoes in Honshu and central Honshu. High-Vp and Vs regions extend beneath the Kinki, Shikoku, and eastern Kyushu regions where the PHS plates subduct. High-Vp/Vs regions are distributed across western Hokkaido, central Honshu,

At a depth of 90 km, low-Vp and low-Vs regions exist beneath the volcanoes beneath Hokkaido and Honshu. High-Vp and Vs regions extend to the east of northeastern Japan where the PAC plate subducts. High-Vp/Vs regions cover northern and

**3.3 Velocity structure beneath the Pacific Ocean off northeastern Japan beneath** 

At a depth of 10 km, a low-Vp and low-Vs zone extends along the coast of the PO in the northeastern Honshu. A high-Vp and high-Vs zone exists between the longitudes of 142 and 143°. East of longitude of 143° (**Figure 6A** and **B**), low-Vp, and low-Vs zone shows again. Vp/Vs is generally low except in some small regions.

At a depth of 20 km, a high-Vp and high-Vs zone extends along the coast of the PO in the northeastern Honshu, in contrast to the structure at a depth of 10 km. Low-V zones extend to the east of the high-Vp zone; however, some high-Vp zones exist among the low-Vp zones (**Figure 6C**). High-Vs zones are mixed with minor low-Vs zone off the east of northeastern Honshu, extending to a longitude of 143.5° (**Figure 6D**). This pattern can be seen with Vp at a depth of 10 km. Vp/Vs is also broadly low, and this pattern of Vp/Vs can be seen when the depth is 10 km except

At a depth of 30 km, low-Vp zone extends off the east of northeastern Honshu

Hokkaido. High-Vp zone can be seen along the Japan Trench. Two patches of low-Vs zones exist in the east of northeastern Honshu at latitude of 37–40° and longitude of 142–143° and at latitude of 35–36° and longitude of 141–142°. High-Vp/Vs region is

At a depth of 40 km, low-Vp and low-Vs zones extend between longitude of 142–143° and latitudes of 37–41°. These low-Vp and low-Vs zones extend to the west of the Hidaka Mountains. High-Vp and high-Vs zones can be seen on the east of the low-V zone and reach the east of the Japan Trench. Vp/Vs in this area is moderate

At a depth of 60 km, low-Vp and low-Vs zones extend just off the coast of the PAC in the northeastern Honshu. High-Vp and high-Vs zones extend broadly on the

between longitudes of 142 and 143.5 and to the region off the southeast of

bounded by the low-Vp/Vs region, a north–south "stripe" pattern.

except for some low-Vp/Vs regions with north–south trend.

east of the narrow low-V zone. Vp/Vs in this area is high.

**78**

The station corrections for the final model are shown in **Figure 7**. Red stations denote positive O-C travel times. It means that the modeled velocity is too high due to thick sediment or low-V materials since the calculated travel time is too small. It also depends on the depth of borehole of Hi-net stations. The seismometers of the Hi-net stations are typically deployed at depths of around 100–200 m, and low-Vp sediment materials are estimated beneath the backbone range and back-arc side of Japan. Large station corrections are estimated along the Sea of Japan coast in northeastern Honshu since there are thick sediments, while borehole stations are relatively shallow. For Vs, there are many blue-colored stations meaning that the velocity model is too slow. Large station corrections are also estimated on the Sea of Japan side of northeastern Honshu.

For S-net stations, blue stations can be seen near the coast and the Japan Trench. Red stations are shown between them for both Vp and Vs. It suggests that the seismic velocity model is too slow near the coast and the Japan Trench and too fast between them.

For DONET stations, red stations are shown near the coast and blue stations reside off the coast. It means that the modeled seismic velocity is too high near the coast.

#### **3.6 Movement of hypocenters**

**Figure 8** shows the histogram of the epicentral movement during the iterations. Epicenters determined by NIED F-net and [20] are shifted over 50 km

**Figure 7.** *Station corrections for (a) Vp and (b) Vs.*

#### **Figure 8.**

*Histogram of the earthquake epicentral movements during the inversion. The initial epicenters are determined by (a) NIED Hi-net; (b) NIED Hi-net, S-net, and DONET; (c) NIED F-net; and (d) Ref. [20]. The Hi-net system also uses the seismic stations operated by the other organizations.*

after the inversion. Epicenters determined by NIED Hi-net or by NIED Hi-net, S-net, and DONET are mainly less than 10 km in spite of 11 iterations of inversion.

#### **4. Discussion**

#### **4.1 Expanded resolved zone from the previous studies**

Ref. [14] also clarified the seismic velocity structure beneath the PO at depths of 30–50 km; however, that study could not resolve the shallow structure at depths of 0–20 km since the ray paths, such as head waves, from the oceanic event to the land seismic stations pass through the deep zone. The ray paths from the events to NIED S-net stations run through the shallow part of the PO. In this study, we can clarify the structure at depths of 10–60 km and even east of the Japan Trench at depths of 20–30 km (**Figures 5** and **6**). This is a major improvement enabled by including NIED S-net data

#### **4.2 Characteristic structure of the NS trending high-V and low-V zone off the northeastern Japan**

One important feature is the probable Mesozoic rift structure trending NS from the coast of Tohoku to the west of Hidaka Collision Zone. The recent 2018 Hokkaido Eastern Iburi earthquake (M6.7) (Iburi earthquake) occurred at a depth of around 32 km, which is much deeper than the usual inland crustal earthquake. Unfortunately, the structure beneath the PO between the Honshu and Hokkaido islands at a depth of 20 km is not clear; however, a low-Vp zone at a depth of 30 km in north–south direction between 142 and 143° (**Figure 9**) is resolved. Low-Vp zones also exist west of the Hidaka Mountains and between the Honshu and Hokkaido at the northern extension of this low-V zone, although the high-Vp zone parallel to the Japan Trench along the coast of Honshu and Hokkaido invades the low-Vp zone. The high-Vp zone is consistent with the large positive Bouguer gravity anomaly [22] and large positive aeromagnetic anomaly zones [23]. It implies that high-V mantle mafic material is located in the shallow zone. The depth of the Moho is also shallow near the coast of northern Honshu [24]. The Iburi earthquake may be

**81**

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

related to the reactivation of the rift related to the structure in the upper mantle to

*Map views of (a) Moho depth, (b) aeromagnetism, (c) Bouguer gravity anomaly, Vp perturbation at depths* 

We clarified the seismic velocity structure beneath the Sea of Japan at depths of 10–20 km from offshore Hokkaido to Wakasa Bay (**Figure 6**). The Vp beneath the Okushiri and Sado Islands is low at a depth of 10 km; however, Vp beneath the Sea of Japan is high at depths of 10–35 km. Vp along the coast of Sea of Japan in western Japan gives moderate value. The lithospheric velocity structure in this region is strongly affected by the Mid-Tertiary breakup and formation of the Sea of Japan. Through the reactivation of the younger compressed tectonic terrain, tsunamigenic source faults have been developed. The lithospheric structure provides essential

**4.4 Comparison with the structure obtained by the offshore experiments**

Ref. [25] imaged the bending-shaped low-Vp oceanic crust of PAC plate subducting from the Japan Trench at latitudes of 38–38.5° offshore Miyagi where the rupture of large interplate earthquakes propagated. In this study, low-Vp material is imaged at depths of 40–50 km bounded by the high-Vp materials with a number of earthquakes surrounded with red ellipse in **Figure 10**. It indicates the subducting

The isovelocity contour of Vp = 7.0 km/s lies around depths of 25–40 km. Activesource seismic experiments off Sanriku region imaged the same contour lying at depths of 20–35 km [25] on the west side of Japan Trench, at depths of 15–30 km at the Japan Trench [26], and at depths of 15–25 km in NS direction between Honshu and Japan Trench [27]. The seismic velocity model of this study is relatively slower than those models derived from seismic experiments. The difference may depend on the initial velocity model of the oceanic region being set as the same as the land area in this study. The Moho depth becomes shallower with the EUR crust toward the Japan Trench. The oceanic crust of the PAC plate has also thinner crust than the EUR island arc crust.

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

the lower crust, where it is marked by high-Vp.

*of (d) 20 km and (e) 30 km beneath northern Japan.*

**Figure 9.**

information to infer the structure of faults.

oceanic crust of the PAC plate

**4.3 Characteristic structure along the sea of Japan**

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

#### **Figure 9.**

*Seismic Waves - Probing Earth System*

inversion.

**Figure 8.**

**4. Discussion**

NIED S-net data

**northeastern Japan**

after the inversion. Epicenters determined by NIED Hi-net or by NIED Hi-net, S-net, and DONET are mainly less than 10 km in spite of 11 iterations of

*Histogram of the earthquake epicentral movements during the inversion. The initial epicenters are determined by (a) NIED Hi-net; (b) NIED Hi-net, S-net, and DONET; (c) NIED F-net; and (d) Ref. [20]. The Hi-net* 

Ref. [14] also clarified the seismic velocity structure beneath the PO at depths of 30–50 km; however, that study could not resolve the shallow structure at depths of 0–20 km since the ray paths, such as head waves, from the oceanic event to the land seismic stations pass through the deep zone. The ray paths from the events to NIED S-net stations run through the shallow part of the PO. In this study, we can clarify the structure at depths of 10–60 km and even east of the Japan Trench at depths of 20–30 km (**Figures 5** and **6**). This is a major improvement enabled by including

**4.2 Characteristic structure of the NS trending high-V and low-V zone off the** 

One important feature is the probable Mesozoic rift structure trending NS from the coast of Tohoku to the west of Hidaka Collision Zone. The recent 2018 Hokkaido Eastern Iburi earthquake (M6.7) (Iburi earthquake) occurred at a depth of around 32 km, which is much deeper than the usual inland crustal earthquake. Unfortunately, the structure beneath the PO between the Honshu and Hokkaido islands at a depth of 20 km is not clear; however, a low-Vp zone at a depth of 30 km in north–south direction between 142 and 143° (**Figure 9**) is resolved. Low-Vp zones also exist west of the Hidaka Mountains and between the Honshu and Hokkaido at the northern extension of this low-V zone, although the high-Vp zone parallel to the Japan Trench along the coast of Honshu and Hokkaido invades the low-Vp zone. The high-Vp zone is consistent with the large positive Bouguer gravity anomaly [22] and large positive aeromagnetic anomaly zones [23]. It implies that high-V mantle mafic material is located in the shallow zone. The depth of the Moho is also shallow near the coast of northern Honshu [24]. The Iburi earthquake may be

**4.1 Expanded resolved zone from the previous studies**

*system also uses the seismic stations operated by the other organizations.*

**80**

*Map views of (a) Moho depth, (b) aeromagnetism, (c) Bouguer gravity anomaly, Vp perturbation at depths of (d) 20 km and (e) 30 km beneath northern Japan.*

related to the reactivation of the rift related to the structure in the upper mantle to the lower crust, where it is marked by high-Vp.

#### **4.3 Characteristic structure along the sea of Japan**

We clarified the seismic velocity structure beneath the Sea of Japan at depths of 10–20 km from offshore Hokkaido to Wakasa Bay (**Figure 6**). The Vp beneath the Okushiri and Sado Islands is low at a depth of 10 km; however, Vp beneath the Sea of Japan is high at depths of 10–35 km. Vp along the coast of Sea of Japan in western Japan gives moderate value. The lithospheric velocity structure in this region is strongly affected by the Mid-Tertiary breakup and formation of the Sea of Japan. Through the reactivation of the younger compressed tectonic terrain, tsunamigenic source faults have been developed. The lithospheric structure provides essential information to infer the structure of faults.

#### **4.4 Comparison with the structure obtained by the offshore experiments**

Ref. [25] imaged the bending-shaped low-Vp oceanic crust of PAC plate subducting from the Japan Trench at latitudes of 38–38.5° offshore Miyagi where the rupture of large interplate earthquakes propagated. In this study, low-Vp material is imaged at depths of 40–50 km bounded by the high-Vp materials with a number of earthquakes surrounded with red ellipse in **Figure 10**. It indicates the subducting oceanic crust of the PAC plate

The isovelocity contour of Vp = 7.0 km/s lies around depths of 25–40 km. Activesource seismic experiments off Sanriku region imaged the same contour lying at depths of 20–35 km [25] on the west side of Japan Trench, at depths of 15–30 km at the Japan Trench [26], and at depths of 15–25 km in NS direction between Honshu and Japan Trench [27]. The seismic velocity model of this study is relatively slower than those models derived from seismic experiments. The difference may depend on the initial velocity model of the oceanic region being set as the same as the land area in this study. The Moho depth becomes shallower with the EUR crust toward the Japan Trench. The oceanic crust of the PAC plate has also thinner crust than the EUR island arc crust.

**Figure 10.**

*Vertical cross section beneath the Pacific Ocean off Miyagi in WNW-ESE direction. Black circle shows the relocated hypocenters used for seismic tomography in this study.*

#### **4.5 Comparison of velocity structure on the coseismic slip plane of the Tohokuoki event**

**Figure 11** shows the Vp perturbation just above the upper boundary of the PAC plate within the overriding EUR plate. The plane with the upper side at surface has a dip angle of 15°. Reference [28] also showed the Vp perturbation [29] above the upper boundary of the subducting PAC slab and three low-V zone offshore Sanriku, Miyagi, and Ibaraki. In our results, we obtain velocity structure in fine scale; however, we do not estimate the shallow structure along the Japan Trench. We obtain the broad low-Vp and low-Vp/Vs zone within the overriding EUR plate between the Japan Trench and Honshu. A high-Vp and slightly high-Vp/Vs zone exists on the

#### **Figure 11.**

*Vp perturbation on the plane just above the upper boundary of the PAC plate within the overriding EUR plate. The plane has strike with S17degW from the point with a longitude of 144.5 and a latitude of 41.0 with dip angle of 12 deg. The depth of the upper edge of the plane is 10 km.*

**83**

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

west side of the low-Vp and low-Vp/Vs zone. There are some small high-V zones

**Figure 12** also shows the Vp perturbation and Vp/Vs on the coseismic plane of the Tohoku-oki event [30]. We do not obtain the shallow structure along the Japan Trench although the extremely large slip of the Tohoku-oki event is estimated near the Japan Trench. The western edge of the large slip zone is consistent with the high-Vp zone; however, the surrounding region has low-Vp and low-Vp/Vs. Low-Vp/Vs material is difficult to deform so that it can generate large elastic waves if it fails. Low-Vp/Vs on the coseismic slip region may be one of the reasons for the

We conducted the seismic tomography for entire Japanese Islands including oceanic area. This is the first tomographic study to use the data from NIED S-net. The hypocenters of oceanic events are greatly improved using the S-net data. We also obtain the detailed seismic velocity structure beneath the PO at depths of 10–60 km. Low-Vp and low-Vs zones are revealed between 142 and 143° at a depth of 30 km and in western Hokkaido where the Eastern Iburi Earthquake in 2018 occurred. The lithospheric velocity structure on the coast of Sea of Japan on Honshu is strongly affected by the Mid-Tertiary breakup and formation of the Sea of Japan. Tsunamigenic source faults have been developed through the reactivation of the younger compression. Subducting low-V oceanic crust is imaged within the mantle of overriding EUR and subducting oceanic PAC plate. The coseismic slip plane of the Tohoku-oki event has low-Vp/Vs; however, the shallow structure along the Japan Trench will be improved in the future with increased data. Previous seismic reflection and refraction studies found the oceanic crust at the uppermost part of the PAC

within the low-V zone near the hypocenter of the Tohoku-oki event.

*(a) Vp perturbation and (b) Vp/Vs on the coseismic slip plane [30].*

extreme size of the Tohoku-oki event.

**5. Conclusion**

**Figure 12.**

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

**Figure 12.** *(a) Vp perturbation and (b) Vp/Vs on the coseismic slip plane [30].*

west side of the low-Vp and low-Vp/Vs zone. There are some small high-V zones within the low-V zone near the hypocenter of the Tohoku-oki event.

**Figure 12** also shows the Vp perturbation and Vp/Vs on the coseismic plane of the Tohoku-oki event [30]. We do not obtain the shallow structure along the Japan Trench although the extremely large slip of the Tohoku-oki event is estimated near the Japan Trench. The western edge of the large slip zone is consistent with the high-Vp zone; however, the surrounding region has low-Vp and low-Vp/Vs. Low-Vp/Vs material is difficult to deform so that it can generate large elastic waves if it fails. Low-Vp/Vs on the coseismic slip region may be one of the reasons for the extreme size of the Tohoku-oki event.

#### **5. Conclusion**

*Seismic Waves - Probing Earth System*

**oki event**

**Figure 10.**

**82**

**Figure 11.**

*Vp perturbation on the plane just above the upper boundary of the PAC plate within the overriding EUR plate. The plane has strike with S17degW from the point with a longitude of 144.5 and a latitude of 41.0 with dip* 

**4.5 Comparison of velocity structure on the coseismic slip plane of the Tohoku-**

*Vertical cross section beneath the Pacific Ocean off Miyagi in WNW-ESE direction. Black circle shows the* 

*relocated hypocenters used for seismic tomography in this study.*

**Figure 11** shows the Vp perturbation just above the upper boundary of the PAC plate within the overriding EUR plate. The plane with the upper side at surface has a dip angle of 15°. Reference [28] also showed the Vp perturbation [29] above the upper boundary of the subducting PAC slab and three low-V zone offshore Sanriku, Miyagi, and Ibaraki. In our results, we obtain velocity structure in fine scale; however, we do not estimate the shallow structure along the Japan Trench. We obtain the broad low-Vp and low-Vp/Vs zone within the overriding EUR plate between the Japan Trench and Honshu. A high-Vp and slightly high-Vp/Vs zone exists on the

*angle of 12 deg. The depth of the upper edge of the plane is 10 km.*

We conducted the seismic tomography for entire Japanese Islands including oceanic area. This is the first tomographic study to use the data from NIED S-net. The hypocenters of oceanic events are greatly improved using the S-net data. We also obtain the detailed seismic velocity structure beneath the PO at depths of 10–60 km. Low-Vp and low-Vs zones are revealed between 142 and 143° at a depth of 30 km and in western Hokkaido where the Eastern Iburi Earthquake in 2018 occurred. The lithospheric velocity structure on the coast of Sea of Japan on Honshu is strongly affected by the Mid-Tertiary breakup and formation of the Sea of Japan. Tsunamigenic source faults have been developed through the reactivation of the younger compression. Subducting low-V oceanic crust is imaged within the mantle of overriding EUR and subducting oceanic PAC plate. The coseismic slip plane of the Tohoku-oki event has low-Vp/Vs; however, the shallow structure along the Japan Trench will be improved in the future with increased data. Previous seismic reflection and refraction studies found the oceanic crust at the uppermost part of the PAC plate with Vp of approximately 6–7 km/s; however, the seismic tomography with NIED S-net clarified the 6–7 km/s Vp zone at depths of 25–40 km. The result may depend on the initial velocity model beneath the PO, which was the same initial model as the land area in this study. Applying the initial velocity model derived from the refraction or reflection seismology would improve the results beneath the ocean in the future.

### **Acknowledgements**

We used the seismic data provided by the National Research Institute for Earth Science and Disaster Resilience, the Japan Meteorological Agency, Hokkaido University, Hirosaki University, Tohoku University, the University of Tokyo, Nagoya University, Kyoto University, Kochi University, Kyushu University, Kagoshima University, the National Institute of Advanced Industrial Science and Technology, the Geographical Survey Institute, Tokyo Metropolis, Shizuoka Prefecture, Hot Springs Research Institute of Kanagawa Prefecture, Yokohama City, and Japan Agency for Marine-Earth Science and Technology. This study was supported by the project on the Operation of Seismograph Networks for NIED. We thank academic editor Masaki Kanao for checking and commenting on our manuscript. We also thank David Shelly and Tomoko E. Yano for their helpful comments and improvement of our manuscript. Some of the figures were drawn using Generic Mapping Tools software [31] and the software for viewing 3D velocity structures beneath whole Japan Islands [32]. This work was financially supported in part by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and by the Council for Science, Technology and Innovation (CSTI) through the Cross-ministerial Strategic Innovation Promotion Program (SIP), entitled "Enhancement of societal resiliency against natural disasters" (Funding agency: Japan Science Technology Agency).

**85**

**Author details**

Japan

Makoto Matsubara1

Toshihiko Kanazawa4

and Shin'ichiro Kamiya1

\*, Hiroshi Sato2

\*Address all correspondence to: mkmatsu@bosai.go.jp

provided the original work is properly cited.

, Narumi Takahashi1

, Kenji Uehira1

1 National Research Institute for Earth Science and Disaster Resilience, Tsukuba,

3 Ministry of Education, Culture, Sports, Science and Technology, Chiyoda, Japan

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

4 Association for the Development of Earthquake Prediction, Chiyoda, Japan

5 Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

2 Earthquake Research Institute, The University of Tokyo, Bunkyo, Japan

, Masashi Mochizuki3

, Kensuke Suzuki5

,

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

#### **Author details**

*Seismic Waves - Probing Earth System*

ocean in the future.

**Acknowledgements**

plate with Vp of approximately 6–7 km/s; however, the seismic tomography with NIED S-net clarified the 6–7 km/s Vp zone at depths of 25–40 km. The result may depend on the initial velocity model beneath the PO, which was the same initial model as the land area in this study. Applying the initial velocity model derived from the refraction or reflection seismology would improve the results beneath the

We used the seismic data provided by the National Research Institute for Earth Science and Disaster Resilience, the Japan Meteorological Agency, Hokkaido University, Hirosaki University, Tohoku University, the University of Tokyo, Nagoya University, Kyoto University, Kochi University, Kyushu University, Kagoshima University, the National Institute of Advanced Industrial Science and Technology, the Geographical Survey Institute, Tokyo Metropolis, Shizuoka Prefecture, Hot Springs Research Institute of Kanagawa Prefecture, Yokohama City, and Japan Agency for Marine-Earth Science and Technology. This study was supported by the project on the Operation of Seismograph Networks for NIED. We thank academic editor Masaki Kanao for checking and commenting on our manuscript. We also thank David Shelly and Tomoko E. Yano for their helpful comments and improvement of our manuscript. Some of the figures were drawn using Generic Mapping Tools software [31] and the software for viewing 3D velocity structures beneath whole Japan Islands [32]. This work was financially supported in part by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) and by the Council for Science, Technology and Innovation (CSTI) through the Cross-ministerial Strategic Innovation Promotion Program (SIP), entitled "Enhancement of societal resiliency against natural disasters" (Funding agency: Japan Science Technology

**84**

Agency).

Makoto Matsubara1 \*, Hiroshi Sato2 , Kenji Uehira1 , Masashi Mochizuki3 , Toshihiko Kanazawa4 , Narumi Takahashi1 , Kensuke Suzuki5 and Shin'ichiro Kamiya1

1 National Research Institute for Earth Science and Disaster Resilience, Tsukuba, Japan


\*Address all correspondence to: mkmatsu@bosai.go.jp

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **References**

[1] National Research Institute for Earth Science and Disaster Resilience, NIED Hi-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0003

[2] Obara K, Kasahara K, Hori S, Okada Y. A densely distributed highsensitivity seismograph network in Japan: Hi-net by National Research Institute for Earth Science and Disaster Prevention. Review of Scientific Instruments. 2005;**76**:021301. DOI: 10.1063/1.1854197

[3] National Research Institute for Earth Science and Disaster Resilience, NIED F-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0005

[4] Okada Y, Kasahara K, Hori S, Obara K, Sekiguchi S, Fujiwara H, et al. Recent progress of seismic observation networks in Japan-Hi-net, F-net, K-NET and KiK-NET. Research News Earth Planets Space. 2004;**56**:xv-xxviii

[5] National Research Institute for Earth Science and Disaster Resilience, NIED DONET, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0008

[6] National Research Institute for Earth Science and Disaster Resilience, NIED S-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0007

[7] Kanazawa T. Japan trench earthquake and tsunami monitoring network of cable-linked 150 ocean bottom observatories and its impact to earth disaster science. In: IEEE International Underwater Technology Symposium (UT). IEEE; 2013. pp. 1, 2013-5

[8] Uehira K, Kanazawa T, Mochizuki M, Fujimoto H, Noguchi S, Shinbo T,

et al. Outline of seafloor observation network for earthquakes and tsunamis along the Japna trench (S-net). EGU General Assembly. 2016;**2016**:EGU2016-EG13832

[9] National Research Institute for Earth Science and Disaster Resilience, NIED K-NET, KiK-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0004

[10] National Research Institute for Earth Science and Disaster Resilience, NIED V-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0006

[11] Zhao D, Hasegawa A, Horiuchi S. Tomographic imaging of P and S wave velocity structure beneath northeastern Japan. Journal of Geophysical Research. 1992;**97**:19,909-19,928

[12] Matsubara M, Obara K, Kasahara K. Three-dimensional P- and S-wave velocity structures beneath the Japan Islands obtained by high-density seismic stations by seismic tomography. Tectonophysics. 2008;**454**:86-103. DOI: 10.1016/j.tecto.2008.04.016

[13] Matsubara M, Obara K. The 2011 off the Pacific coast of Tohoku earthquake related to a strong velocity gradient with the Pacific plate. Earth, Planets and Space. 2011;**63**:663-667

[14] Matsubara M, Sato H, Uehira K, Mochizuki M, Kanazawa T. Threedimensional seismic velocity structure beneath Japanese Islands and surroundings based on NIED seismic networks using both inland and offshore events. Journal of Disaster Research. 2017;**12**:844-857. DOI: 10.20965/jdr.2017.p0844

[15] Matsubara M, Hirata N, Sato H, Sakai S. Lower crustal fluid distribution in the northeastern Japan arc revealed by

**87**

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic…*

of Japan. Digital Geoscience Map P-6. Geological Survey of Japan. 2005

[24] Matsubara M, Sato H, Ishiyama T, Van Horne AD. Configuration of the Moho discontinuity beneath the Japanese Islands derived from threedimensional seismic tomography. Tectonophysics. 2017;**710-711**:97-107. DOI: 10.1016/j.tecto.2016.11.025

[25] Ito A, Fujie G, Miura S, Kodaira S, Kaneda Y, Hino R. Bending of the subducting oceanic plate and its implication for rupture propagation of large interplate earthquakes off Miyagi, Japan, in the Japan trench subduction zone. Geophysical

Research Letters. 2005;**32**:L05310. DOI:

[26] Obana K, Fujie G, Takahashi T, Yamamoto Y, Tonegawa T, Miura S, et al. Seismic velocity structure and its implications for oceanic mantle hydration in the trench-outer

Geophysical Journal International. 2019;**217**:1629-1642. DOI: 10.1093/gji/

[27] Fujie G, Kodaira S, Yamashita M, Sato T, Takahashi T, Takahashi N. Systematic changes in the incoming

10.1029/2004GL022307

rise of the Japan trench.

plate structure at the Kuril trench. Geophysical Research Letters. 2012;**40**:88-93. DOI: 10.1029/2012GL054340

10.1029/2011GL048408

[28] Zhao D, Huang Z, Umino N, Hasegawa A, Kanamori H. Structural heterogeneity in the megathrust zone and mechanism of the 2011 Tohoku-oki earthquake (Mw 9.0). Geophysical Research Letters. 2011;**38**:L17308. DOI:

[29] Huang Z, Zhao D. Mechanism of the 2011 Tohoku-oki earthquake (Mw 9.0) and tsunami: Insight from seismic tomography. Journal of Asian Earth Sciences. 2013;**70-71**:160-168

ggz099

*DOI: http://dx.doi.org/10.5772/intechopen.86936*

high resolution 3D seismic tomography. Tectonophysics. 2004;**388**:33-45. DOI:

[16] Matsubara M, Hayashi H, Obara K, Kasahara K. Low-velocity oceanic crust at the top of the Philippine Sea and Pacific plates beneath the Kanto region, Central Japan, imaged by seismic tomography. Journal of Geophysical Research. 2005;**110**:B12304. DOI:

10.1016/j.tecto.2004.07.046

10.1029/2005JB003673

Prevention. 1984;**53**:1-88

p. 386

[17] Nolet G. Seismic Tomography. D. Reidel Publishing Company; 1987.

[18] Ukawa M, Ishida M, Matsumura S, Kasahara K. Hypocenter determination method of the Kanto-Tokai observational network for microearthquakes (in Japanese with English abstract). Research Notes National Research Center Disaster

[19] Matsubara M, Obara K, Kasahara K.

[20] Asano Y, Saito T, Ito Y, Shiomi K, Hirose H, Matsumoto T, et al. Spatial distribution and focal mechanisms of aftershocks of the 2011 off the Pacific coast of Tohoku earthquake. Earth, Planets and Space. 2011;**63**:669-673. DOI: 10.5047/eps.2011.05.018

[21] Inoue H, Fukao Y, Tanabe K, Ogata Y. Whole mantle P-wave travel time tomography. Physics of the Earth and Planetary Interiors. 1990;**59**:294-328

[22] Geological Survey of Japan. Gravity Database of Japan. DVD edition, Digital Geoscience Map P-2. Geological Survey

of Japan, AIST. 2013

[23] Nakatsuka T, Okuma S.

Aeromagnetic Anomalies Database

High-Vp/vs zone accompanying non-volcanic tremors and slow slip events beneath southwestern Japan. Tectonophysics. 2009;**472**:6-17. DOI:

10.1016/j.tecto.2008.06.013

*Seismic Velocity Structure in and around the Japanese Island Arc Derived from Seismic… DOI: http://dx.doi.org/10.5772/intechopen.86936*

high resolution 3D seismic tomography. Tectonophysics. 2004;**388**:33-45. DOI: 10.1016/j.tecto.2004.07.046

[16] Matsubara M, Hayashi H, Obara K, Kasahara K. Low-velocity oceanic crust at the top of the Philippine Sea and Pacific plates beneath the Kanto region, Central Japan, imaged by seismic tomography. Journal of Geophysical Research. 2005;**110**:B12304. DOI: 10.1029/2005JB003673

[17] Nolet G. Seismic Tomography. D. Reidel Publishing Company; 1987. p. 386

[18] Ukawa M, Ishida M, Matsumura S, Kasahara K. Hypocenter determination method of the Kanto-Tokai observational network for microearthquakes (in Japanese with English abstract). Research Notes National Research Center Disaster Prevention. 1984;**53**:1-88

[19] Matsubara M, Obara K, Kasahara K. High-Vp/vs zone accompanying non-volcanic tremors and slow slip events beneath southwestern Japan. Tectonophysics. 2009;**472**:6-17. DOI: 10.1016/j.tecto.2008.06.013

[20] Asano Y, Saito T, Ito Y, Shiomi K, Hirose H, Matsumoto T, et al. Spatial distribution and focal mechanisms of aftershocks of the 2011 off the Pacific coast of Tohoku earthquake. Earth, Planets and Space. 2011;**63**:669-673. DOI: 10.5047/eps.2011.05.018

[21] Inoue H, Fukao Y, Tanabe K, Ogata Y. Whole mantle P-wave travel time tomography. Physics of the Earth and Planetary Interiors. 1990;**59**:294-328

[22] Geological Survey of Japan. Gravity Database of Japan. DVD edition, Digital Geoscience Map P-2. Geological Survey of Japan, AIST. 2013

[23] Nakatsuka T, Okuma S. Aeromagnetic Anomalies Database of Japan. Digital Geoscience Map P-6. Geological Survey of Japan. 2005

[24] Matsubara M, Sato H, Ishiyama T, Van Horne AD. Configuration of the Moho discontinuity beneath the Japanese Islands derived from threedimensional seismic tomography. Tectonophysics. 2017;**710-711**:97-107. DOI: 10.1016/j.tecto.2016.11.025

[25] Ito A, Fujie G, Miura S, Kodaira S, Kaneda Y, Hino R. Bending of the subducting oceanic plate and its implication for rupture propagation of large interplate earthquakes off Miyagi, Japan, in the Japan trench subduction zone. Geophysical Research Letters. 2005;**32**:L05310. DOI: 10.1029/2004GL022307

[26] Obana K, Fujie G, Takahashi T, Yamamoto Y, Tonegawa T, Miura S, et al. Seismic velocity structure and its implications for oceanic mantle hydration in the trench-outer rise of the Japan trench. Geophysical Journal International. 2019;**217**:1629-1642. DOI: 10.1093/gji/ ggz099

[27] Fujie G, Kodaira S, Yamashita M, Sato T, Takahashi T, Takahashi N. Systematic changes in the incoming plate structure at the Kuril trench. Geophysical Research Letters. 2012;**40**:88-93. DOI: 10.1029/2012GL054340

[28] Zhao D, Huang Z, Umino N, Hasegawa A, Kanamori H. Structural heterogeneity in the megathrust zone and mechanism of the 2011 Tohoku-oki earthquake (Mw 9.0). Geophysical Research Letters. 2011;**38**:L17308. DOI: 10.1029/2011GL048408

[29] Huang Z, Zhao D. Mechanism of the 2011 Tohoku-oki earthquake (Mw 9.0) and tsunami: Insight from seismic tomography. Journal of Asian Earth Sciences. 2013;**70-71**:160-168

**86**

*Seismic Waves - Probing Earth System*

DOI: 10.17598/NIED.0003

**References**

10.1063/1.1854197

DOI: 10.17598/NIED.0005

DOI: 10.17598/NIED.0008

DOI: 10.17598/NIED.0007

[4] Okada Y, Kasahara K, Hori S,

[2] Obara K, Kasahara K, Hori S, Okada Y. A densely distributed highsensitivity seismograph network in Japan: Hi-net by National Research Institute for Earth Science and Disaster Prevention. Review of Scientific Instruments. 2005;**76**:021301. DOI:

[1] National Research Institute for Earth Science and Disaster Resilience, NIED Hi-net, National Research Institute for Earth Science and Disaster Resilience.

et al. Outline of seafloor observation

[9] National Research Institute for Earth Science and Disaster Resilience, NIED K-NET, KiK-net, National Research Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0004

[10] National Research Institute for Earth Science and Disaster Resilience, NIED V-net, National Research

Institute for Earth Science and Disaster Resilience. DOI: 10.17598/NIED.0006

[11] Zhao D, Hasegawa A, Horiuchi S. Tomographic imaging of P and S wave velocity structure beneath northeastern Japan. Journal of Geophysical Research.

[12] Matsubara M, Obara K, Kasahara K. Three-dimensional P- and S-wave velocity structures beneath the Japan Islands obtained by high-density seismic stations by seismic tomography. Tectonophysics. 2008;**454**:86-103. DOI:

[13] Matsubara M, Obara K. The 2011 off the Pacific coast of Tohoku earthquake related to a strong velocity gradient with the Pacific plate. Earth, Planets and

[14] Matsubara M, Sato H, Uehira K, Mochizuki M, Kanazawa T. Threedimensional seismic velocity structure beneath Japanese Islands and surroundings based on NIED seismic networks using both inland and offshore events. Journal of Disaster Research. 2017;**12**:844-857. DOI:

[15] Matsubara M, Hirata N, Sato H, Sakai S. Lower crustal fluid distribution in the northeastern Japan arc revealed by

1992;**97**:19,909-19,928

10.1016/j.tecto.2008.04.016

Space. 2011;**63**:663-667

10.20965/jdr.2017.p0844

network for earthquakes and tsunamis along the Japna trench (S-net). EGU General Assembly. 2016;**2016**:EGU2016-EG13832

[3] National Research Institute for Earth Science and Disaster Resilience, NIED F-net, National Research Institute for Earth Science and Disaster Resilience.

Obara K, Sekiguchi S, Fujiwara H, et al. Recent progress of seismic observation networks in Japan-Hi-net, F-net, K-NET and KiK-NET. Research News Earth Planets Space. 2004;**56**:xv-xxviii

[5] National Research Institute for Earth Science and Disaster Resilience, NIED DONET, National Research Institute for Earth Science and Disaster Resilience.

[6] National Research Institute for Earth Science and Disaster Resilience, NIED S-net, National Research Institute for Earth Science and Disaster Resilience.

[7] Kanazawa T. Japan trench earthquake and tsunami monitoring network of cable-linked 150 ocean bottom observatories and its impact to earth disaster science. In: IEEE International Underwater Technology Symposium (UT). IEEE; 2013. pp. 1, 2013-5

[8] Uehira K, Kanazawa T, Mochizuki M, Fujimoto H, Noguchi S, Shinbo T, [30] Suzuki W, Aoi S, Sekiguchi H, Kunugi T. Rupture process of the 2011 Tohoku-Oki mega-thrust earthquake (M9.0) inverted from strong-motion data. Geophysical Research Letters. 2011;**38**:L00G16. DOI: 10.1029/2011GL049136

[31] Wessel P, WHF S. New version of generic mapping tools released. EOS Transactions. 1995;**79**:329

[32] Matsubara M. Software for viewing 3D velocity structures beneath whole Japan Islands. Report of the National Research Institute for Earth Science and Disaster Prevention. 2010;**76**:1-9

**89**

aspect).

**Chapter 6**

**Abstract**

Earthquakes

changes of stress before strong EQs can be expected.

induction vector, earthquake precursor

**1. Introduction**

**Keywords:** geomagnetic field, lithosphere emission, conductivity structure,

One of the long lasting challenges for the Earth sciences is earthquake (EQ ) prediction. EQ precursors deliver unique information which is necessary for the solution of two interconnected fundamental problems—EQ prediction (humanitarian practical aspect) and support to the development of EQ theory (scientific

The history of the EQ precursor study goes back to antiquity. But even now their study remains purely empirical, and any precursor even recorded with perfect instrument can be treated as not related with seismicity (skepticism to prediction widely spread now), and it is difficult to prove that it is genuine EQ precursor because physics of EQ preparation process is still not well understood. The causes of such situation are (1) the complexity of the real Earth and processes

Low-Frequency Electromagnetic

*Igor I. Rokityansky, Valeriia I. Babak and Artem V. Tereshyn*

We consider two kinds of signals preceding earthquake (EQ ): intensification of internal electromagnetic (EM) field – lithosphere emission (LE) and change of the Earth interior response function (RF). Several cases of LE before strong EQs were reviewed and analyzed, and preliminary portrait of LE precursor was compiled. LE can appear several times with lead time month(s), weeks, days, and hours and can attain amplitude of several hundreds of nT which not uniformly decreases with increasing distance from the source. Typical LE frequency content/maximum is 0.01–0.5 Hz. Data of 19 Japanese geomagnetic observatories for 20 years preceding the Tohoku EQ on March 11, 2011 were analyzed, and RFs (mainly induction vector) were calculated. At six observatories in 2008–2010, anomalous variations of RF were separated which can be identified as middle-term precursors. Applying the original method developed in Ukraine, a short-term two-month-long precursor of bay-like form was separated by phase data of observatory KNZ in the Boso peninsula where electrical conductivity anomaly was also discovered. Hypothetical explanation based on tectonic data is advanced: Boso anomaly connects two largescale conductors—Pacific seawater and deep magma reservoir beneath a volcanic belt. Between two so different conductors, an unstable transition zone sensitive to

Signals Observed before Strong

#### **Chapter 6**

*Seismic Waves - Probing Earth System*

[30] Suzuki W, Aoi S, Sekiguchi H, Kunugi T. Rupture process of the 2011 Tohoku-Oki mega-thrust earthquake (M9.0) inverted from strong-motion data. Geophysical Research Letters. 2011;**38**:L00G16. DOI:

[31] Wessel P, WHF S. New version of generic mapping tools released. EOS

[32] Matsubara M. Software for viewing 3D velocity structures beneath whole Japan Islands. Report of the National Research Institute for Earth Science and

Disaster Prevention. 2010;**76**:1-9

10.1029/2011GL049136

Transactions. 1995;**79**:329

**88**

## Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes

*Igor I. Rokityansky, Valeriia I. Babak and Artem V. Tereshyn*

#### **Abstract**

We consider two kinds of signals preceding earthquake (EQ ): intensification of internal electromagnetic (EM) field – lithosphere emission (LE) and change of the Earth interior response function (RF). Several cases of LE before strong EQs were reviewed and analyzed, and preliminary portrait of LE precursor was compiled. LE can appear several times with lead time month(s), weeks, days, and hours and can attain amplitude of several hundreds of nT which not uniformly decreases with increasing distance from the source. Typical LE frequency content/maximum is 0.01–0.5 Hz. Data of 19 Japanese geomagnetic observatories for 20 years preceding the Tohoku EQ on March 11, 2011 were analyzed, and RFs (mainly induction vector) were calculated. At six observatories in 2008–2010, anomalous variations of RF were separated which can be identified as middle-term precursors. Applying the original method developed in Ukraine, a short-term two-month-long precursor of bay-like form was separated by phase data of observatory KNZ in the Boso peninsula where electrical conductivity anomaly was also discovered. Hypothetical explanation based on tectonic data is advanced: Boso anomaly connects two largescale conductors—Pacific seawater and deep magma reservoir beneath a volcanic belt. Between two so different conductors, an unstable transition zone sensitive to changes of stress before strong EQs can be expected.

**Keywords:** geomagnetic field, lithosphere emission, conductivity structure, induction vector, earthquake precursor

#### **1. Introduction**

One of the long lasting challenges for the Earth sciences is earthquake (EQ ) prediction. EQ precursors deliver unique information which is necessary for the solution of two interconnected fundamental problems—EQ prediction (humanitarian practical aspect) and support to the development of EQ theory (scientific aspect).

The history of the EQ precursor study goes back to antiquity. But even now their study remains purely empirical, and any precursor even recorded with perfect instrument can be treated as not related with seismicity (skepticism to prediction widely spread now), and it is difficult to prove that it is genuine EQ precursor because physics of EQ preparation process is still not well understood. The causes of such situation are (1) the complexity of the real Earth and processes in it, (2) the absence of direct information from the place of EQ preparation, nucleation, and occurrence in the Earth interior. Nevertheless, consider the unique case of the successful EQ prediction—Haicheng prediction.

#### **1.1 Haicheng EQM7.3**

The Haicheng EQM7.3 occurred on February 4, 1975 at 19:35 local time in northeast China. After 1965, activation of seismicity occurred in an area of 120 km to SSW from Beijing with several destructive EQsM > 6. After this *long-term prediction*, the Chinese government greatly strengthened EQ study and precursor monitoring (telluric currents, well water, animal behavior, and other phenomena related with EQ ) attaching to observation experts and also amateurs and scholars. Many precursors were observed in 1973 and 1974 in a large area of 200 × 300 km (*middle-term precursors*) which in December 1974–January 1975 concentrated in a smaller area. In January 1975, quiescence of seismicity was observed but anomalies of groundwater, telluric currents, radon, tilt, animal behavior, etc. increased till January 23 (*shortterm precursors*), then slightly decreased, and since February 1 rouse in hundreds times. From 16:00, February 3, to 18:30, February 4, 500 EQs with M up to 4.2 occurred in the area between Yingkou and Haicheng cities. They were interpreted as foreshocks of strong EQ. Emergency evacuation was ordered by authorities, and law-abiding Chinese left their houses. At 19:36, a devastating EQ struck dozens of cities including Haicheng with almost 1 million inhabitants. Thousands of buildings collapsed, but hundred thousand lives have been saved by the well-timed prediction. Instructive lessons from successful Haicheng prediction are (1) continuous transition from long−/intermediate-term prediction to short/immediate ones with consistent improvement of expected EQ time, place, and magnitude; (2) close cooperation of authorities, scientists, amateurs, and mass media; and (3) the use of all available precursors, including "nonscientific" ones as animal behavior [1].

Multiparameter monitoring and strong scientific efforts of the last decades reveal some unexpected features of precursors: (1) Long-distance appearance up to thousands km from EQ epicenter. (2) Spatial selectivity: EQ precursors can be observed in some sensitive zones (usually fault zones) and be not observable in vast territories even not far from impending EQ. (3) Spatial–temporal migration of precursors: initially it appears in one locality, and then it appears in the next locality, usually with changed parameters. Such features did not find explanation in the framework of simple dominant ideas in the middle of the twentieth century about geological media. These features evidenced the complexity of geological media, and in the second half of the twentieth century, several new concepts have appeared to explain new data (Sadovsky MA, Varotsos P, Gufeld IL and many others).

For effective EQ prediction, we need automatic system of monitoring, processing, and analysis of all observed precursory parameters, their cross-correlation analysis to estimate probability of expected EQ (taking into account all previous global, regional, and local analyzes). High-level scientific team must keep contact with decision-making authorities for providing public announcement of the EQ prediction and plan of emergency measures. Such system needs great funds. Some elements of such system are created in few regions (California, China, ex-USSR countries).

#### **1.2 Goal and scope of the chapter**

Multitude of EQ precursors is the unique base for EQ prediction. Complexity of the earth and poor understanding of seismicity process enforce us to use as many

**91**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

kinds of precursors as possible. Two approaches are perspective for the fishing of the precursory signals from geomagnetic data: (1) Direct observation of the lithosphere emission (LE) of the internal electromagnetic fields arising in the course of EQ preparation and nucleation process and (2) transformation of the time series of the observed three components of geomagnetic field into time series of response

In the next sub-section, we review few case stories of the most reliable records of

In Section 2, we shortly outline the rather sophisticated methodology of response function (RF) approach referring for details to few monographs [2–5]. In Sections 3 and 4, we apply RF method to the Japanese geomagnetic observatories data in the attempt to separate the precursors of great Tohoku EQM9 11.03.2011, wherein obtained quite reliable result on the Boso conductivity anomaly

In Section 6, we summarize the results and give the recommendations for the

There are many reports on LE registration, in particular before EQs. Consider fortunate cases when EM observations turned out to be located in the places where LE field was well above magnetotelluric (MT) field+noise background and can be

Geomagnetic observatory in the city of Kodiak was located in the distance of 440 km from the epicenter of the EQ and only in 30 km from the fault zone along which displacement occurred. The full field proton magnetometer recorded several magnetic disturbances. The strongest one with intensity 100nT appeared 1 h 06 min

One of the most convincing cases of LE precursors was recorded before that EQ [7]. The monitoring system of Stanford University (created for traffic noise study) operated since October 1987 at the distance of 7 km from the future EQ epicenter. The system included induction coils and special computer which calculated half-hourly averages of the magnetic field power spectra in each of nine narrow

During 23 months record was normal with low noise. After September 12, 1989, anomalous signal began to appear in two frequency bands: 0.05–0.1 and 0.1–0.2 Hz and grew up to 1.5 nT. In October 5, a large increase of amplitude appeared at all frequencies with the strongest one at the lowest frequency 0.01 Hz, where it reached 30 times the normal level. On the last several days before EQ, anomaly gradually diminishes (a quiescence!), and 3 h before the EQ, very large amplitude appeared only at periods longer 0.5 Hz, exceptionally large at frequency 0.01 Hz. We must emphasize that instrumentation of Stanford University which allowed to get results every half an hour is very good for LE monitoring. Unfortunately, it did not con-

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

functions of the Earth's interior conductivity.

and advance its tectonic interpretation.

In Section 5, we discuss the results obtained.

**1.3 Case stories of LE records before strong EQs**

*1.3.1 Great Alaska EQM9.2 on March 28, 1964*

*1.3.2 Loma Prieta EQM7.1 on October 18, 1989*

tinue the operation for EQ prediction.

frequency bands covering the overall range 0.01–10 Hz.

improvement of the low-frequency EM precursor study.

ultralow-frequency (ULF) LE.

easily identified.

before the EQ [6].

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

*Seismic Waves - Probing Earth System*

**1.1 Haicheng EQM7.3**

in it, (2) the absence of direct information from the place of EQ preparation, nucleation, and occurrence in the Earth interior. Nevertheless, consider the

The Haicheng EQM7.3 occurred on February 4, 1975 at 19:35 local time in northeast China. After 1965, activation of seismicity occurred in an area of 120 km to SSW from Beijing with several destructive EQsM > 6. After this *long-term prediction*, the Chinese government greatly strengthened EQ study and precursor monitoring (telluric currents, well water, animal behavior, and other phenomena related with EQ ) attaching to observation experts and also amateurs and scholars. Many precursors were observed in 1973 and 1974 in a large area of 200 × 300 km (*middle-term precursors*) which in December 1974–January 1975 concentrated in a smaller area. In January 1975, quiescence of seismicity was observed but anomalies of groundwater, telluric currents, radon, tilt, animal behavior, etc. increased till January 23 (*shortterm precursors*), then slightly decreased, and since February 1 rouse in hundreds times. From 16:00, February 3, to 18:30, February 4, 500 EQs with M up to 4.2 occurred in the area between Yingkou and Haicheng cities. They were interpreted as foreshocks of strong EQ. Emergency evacuation was ordered by authorities, and law-abiding Chinese left their houses. At 19:36, a devastating EQ struck dozens of cities including Haicheng with almost 1 million inhabitants. Thousands of buildings collapsed, but hundred thousand lives have been saved by the well-timed prediction. Instructive lessons from successful Haicheng prediction are (1) continuous transition from long−/intermediate-term prediction to short/immediate ones with consistent improvement of expected EQ time, place, and magnitude; (2) close cooperation of authorities, scientists, amateurs, and mass media; and (3) the use of all available

unique case of the successful EQ prediction—Haicheng prediction.

precursors, including "nonscientific" ones as animal behavior [1].

Multiparameter monitoring and strong scientific efforts of the last decades reveal some unexpected features of precursors: (1) Long-distance appearance up to thousands km from EQ epicenter. (2) Spatial selectivity: EQ precursors can be observed in some sensitive zones (usually fault zones) and be not observable in vast territories even not far from impending EQ. (3) Spatial–temporal migration of precursors: initially it appears in one locality, and then it appears in the next locality, usually with changed parameters. Such features did not find explanation in the framework of simple dominant ideas in the middle of the twentieth century about geological media. These features evidenced the complexity of geological media, and in the second half of the twentieth century, several new concepts have appeared to

explain new data (Sadovsky MA, Varotsos P, Gufeld IL and many others).

For effective EQ prediction, we need automatic system of monitoring, processing, and analysis of all observed precursory parameters, their cross-correlation analysis to estimate probability of expected EQ (taking into account all previous global, regional, and local analyzes). High-level scientific team must keep contact with decision-making authorities for providing public announcement of the EQ prediction and plan of emergency measures. Such system needs great funds. Some elements of such system are created in few regions (California, China, ex-USSR countries).

Multitude of EQ precursors is the unique base for EQ prediction. Complexity of the earth and poor understanding of seismicity process enforce us to use as many

**90**

**1.2 Goal and scope of the chapter**

kinds of precursors as possible. Two approaches are perspective for the fishing of the precursory signals from geomagnetic data: (1) Direct observation of the lithosphere emission (LE) of the internal electromagnetic fields arising in the course of EQ preparation and nucleation process and (2) transformation of the time series of the observed three components of geomagnetic field into time series of response functions of the Earth's interior conductivity.

In the next sub-section, we review few case stories of the most reliable records of ultralow-frequency (ULF) LE.

In Section 2, we shortly outline the rather sophisticated methodology of response function (RF) approach referring for details to few monographs [2–5].

In Sections 3 and 4, we apply RF method to the Japanese geomagnetic observatories data in the attempt to separate the precursors of great Tohoku EQM9 11.03.2011, wherein obtained quite reliable result on the Boso conductivity anomaly and advance its tectonic interpretation.

In Section 5, we discuss the results obtained.

In Section 6, we summarize the results and give the recommendations for the improvement of the low-frequency EM precursor study.

#### **1.3 Case stories of LE records before strong EQs**

There are many reports on LE registration, in particular before EQs. Consider fortunate cases when EM observations turned out to be located in the places where LE field was well above magnetotelluric (MT) field+noise background and can be easily identified.

#### *1.3.1 Great Alaska EQM9.2 on March 28, 1964*

Geomagnetic observatory in the city of Kodiak was located in the distance of 440 km from the epicenter of the EQ and only in 30 km from the fault zone along which displacement occurred. The full field proton magnetometer recorded several magnetic disturbances. The strongest one with intensity 100nT appeared 1 h 06 min before the EQ [6].

#### *1.3.2 Loma Prieta EQM7.1 on October 18, 1989*

One of the most convincing cases of LE precursors was recorded before that EQ [7]. The monitoring system of Stanford University (created for traffic noise study) operated since October 1987 at the distance of 7 km from the future EQ epicenter. The system included induction coils and special computer which calculated half-hourly averages of the magnetic field power spectra in each of nine narrow frequency bands covering the overall range 0.01–10 Hz.

During 23 months record was normal with low noise. After September 12, 1989, anomalous signal began to appear in two frequency bands: 0.05–0.1 and 0.1–0.2 Hz and grew up to 1.5 nT. In October 5, a large increase of amplitude appeared at all frequencies with the strongest one at the lowest frequency 0.01 Hz, where it reached 30 times the normal level. On the last several days before EQ, anomaly gradually diminishes (a quiescence!), and 3 h before the EQ, very large amplitude appeared only at periods longer 0.5 Hz, exceptionally large at frequency 0.01 Hz. We must emphasize that instrumentation of Stanford University which allowed to get results every half an hour is very good for LE monitoring. Unfortunately, it did not continue the operation for EQ prediction.

#### *1.3.3 Caucasus*

Kopytenko et al. [8, 9] developed three-component magnetometers for frequency range 0.005–10 Hz. The first instrument started the record 23 days before destroying Spitak EQM6.9 at 7.41 UT, on December 7, 1988, in geomagnetic observatory at Dusheti, 129 km to the north from the EQ epicenter. It recorded intensive **BLE** which started 4 h prior the EQ (**Figure 1a**, **b**).

In the time interval November 14, 1988 to March 5, 1989 in frequency range 0.1–1 Hz 59 unusual noise-like bursts of LE with an amplitude well higher the background noise (0.03 nT) and the duration ranging from several minutes to several hours (mean duration ≈30 min) were recorded mainly before the strong aftershocks. Decrease in aftershock activities and **BLE** activity was quite synchronous.

The next strong event was Racha EQM6.9 at 9.13 UT, on April 29, 1991, occurred at the epicentral distance of 90 km from Dusheti where no pronounced **BLE** were recorded. It means that Dusheti is not a sensitive place for the EQs in Racha region (effect of spatial selectivity). Kopytenko's team organized **BLE** observations in two field sites Nik and Oni for June–July 1991—the time of Racha aftershock activities. Forty-seven **BLE** with intensity up to 2 nT and duration ranging from several minutes to several hours were observed at both observatories, 23 of them were recorded 1–4 days before the strong aftershock M6.2 on June 15,1991. **Figure 1c** presents **BLE** bursts observed before aftershock M4.0. The distance from the epicenter to Oni was two times smaller than to Nik, but intensity of LE signal at Nik was considerably larger: for H component in 10–20 times, for D in 1.3–2 times, and for Z in 5–7 times. It means strong spatial selectivity of the LE signals preceding EQ [10, 11].

#### **Figure 1.**

*B***LE** *preceded some EQs in Caucasus [8, 9]. (a) Map of seismoactive region with the sites of observation and epicenters (given by stars) of the events discussed in text. (b) Final fragment of B***LE** *record started 4 h before Spitak EQ and abruptly terminated 2 h 48 min before it. (c) Several short B***LE** *bursts records during 33 min before aftershock M4.0 at field stations Nik and Oni located at the distance 34.6 and 16.9 km from the epicenter correspondingly.*

**93**

**Figure 2.**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

Prieta, where the maximum tends to their lowest frequency 0.01 Hz.

In the conclusion we like to emphasize that magnetometers in described studies can register variations in the frequency band of 0.005–10 Hz, but they recorded most intensive **BLE** at the frequencies 0.1–1 Hz that differs from the result in Loma

The island-wide geomagnetic network consisted of three-component geomagnetic observatory LP in the seismically quiet area and seven full field stations equipped by proton magnetometers with 0.1 nT sensitivity and sampling rate of 10 min distributed in areas of high seismicity [12]. Chi-Chi EQM7.6 occurred on September 21, 1999, in the middle of Taiwan. Stations LY turned out to be just near to surface rupture of the EQ along Chelungpu fault and recorded the strongest LE which clearly separated from comparison with records of remote observatory LP. LE begun more than a month before the EQ and attained in maximum 200 nT, and then its amplitudes gradually weakened, and the disturbance level reduced to that of a quiet period almost right after the second strong Chia-Yi EQM6.4 that occurred near the southern end of the Chelungpu fault on October 22, 1999 [12].

In Greece in the early 1980s for the registration of the LE electric components, the so-called seismic electric signals (SES) special network was created by Prof.

*The SES activity on April 19, 1995, before the Grevena-Kozani EQM6.6 on May 13, 1995, recorded in Greece at the IOA observatory at the distance of 80 km from the epicenter with a sampling rate of 1 sample/s: (a) 3 h record with strong SES activity in 6.30–7.40 time interval, (b) is the 5 min fragment of (a), showing both electric and magnetic components in expanded time scale [11]. Amplitudes are given in relative units.*

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

*1.3.4 Taiwan*

*1.3.5 Greece*

In the conclusion we like to emphasize that magnetometers in described studies can register variations in the frequency band of 0.005–10 Hz, but they recorded most intensive **BLE** at the frequencies 0.1–1 Hz that differs from the result in Loma Prieta, where the maximum tends to their lowest frequency 0.01 Hz.

#### *1.3.4 Taiwan*

*Seismic Waves - Probing Earth System*

**BLE** which started 4 h prior the EQ (**Figure 1a**, **b**).

Kopytenko et al. [8, 9] developed three-component magnetometers for frequency range 0.005–10 Hz. The first instrument started the record 23 days before destroying Spitak EQM6.9 at 7.41 UT, on December 7, 1988, in geomagnetic observatory at Dusheti, 129 km to the north from the EQ epicenter. It recorded intensive

In the time interval November 14, 1988 to March 5, 1989 in frequency range 0.1–1 Hz 59 unusual noise-like bursts of LE with an amplitude well higher the background noise (0.03 nT) and the duration ranging from several minutes to several hours (mean duration ≈30 min) were recorded mainly before the strong aftershocks. Decrease in aftershock activities and **BLE** activity was quite synchronous. The next strong event was Racha EQM6.9 at 9.13 UT, on April 29, 1991, occurred at the epicentral distance of 90 km from Dusheti where no pronounced **BLE** were recorded. It means that Dusheti is not a sensitive place for the EQs in Racha region (effect of spatial selectivity). Kopytenko's team organized **BLE** observations in two field sites Nik and Oni for June–July 1991—the time of Racha aftershock activities. Forty-seven **BLE** with intensity up to 2 nT and duration ranging from several minutes to several hours were observed at both observatories, 23 of them were recorded 1–4 days before the strong aftershock M6.2 on June 15,1991. **Figure 1c** presents **BLE** bursts observed before aftershock M4.0. The distance from the epicenter to Oni was two times smaller than to Nik, but intensity of LE signal at Nik was considerably larger: for H component in 10–20 times, for D in 1.3–2 times, and for Z in 5–7 times.

It means strong spatial selectivity of the LE signals preceding EQ [10, 11].

*B***LE** *preceded some EQs in Caucasus [8, 9]. (a) Map of seismoactive region with the sites of observation and epicenters (given by stars) of the events discussed in text. (b) Final fragment of B***LE** *record started 4 h before Spitak EQ and abruptly terminated 2 h 48 min before it. (c) Several short B***LE** *bursts records during 33 min before aftershock M4.0 at field stations Nik and Oni located at the distance 34.6 and 16.9 km from the epicenter* 

*1.3.3 Caucasus*

**92**

**Figure 1.**

*correspondingly.*

The island-wide geomagnetic network consisted of three-component geomagnetic observatory LP in the seismically quiet area and seven full field stations equipped by proton magnetometers with 0.1 nT sensitivity and sampling rate of 10 min distributed in areas of high seismicity [12]. Chi-Chi EQM7.6 occurred on September 21, 1999, in the middle of Taiwan. Stations LY turned out to be just near to surface rupture of the EQ along Chelungpu fault and recorded the strongest LE which clearly separated from comparison with records of remote observatory LP. LE begun more than a month before the EQ and attained in maximum 200 nT, and then its amplitudes gradually weakened, and the disturbance level reduced to that of a quiet period almost right after the second strong Chia-Yi EQM6.4 that occurred near the southern end of the Chelungpu fault on October 22, 1999 [12].

#### *1.3.5 Greece*

In Greece in the early 1980s for the registration of the LE electric components, the so-called seismic electric signals (SES) special network was created by Prof.

#### **Figure 2.**

*The SES activity on April 19, 1995, before the Grevena-Kozani EQM6.6 on May 13, 1995, recorded in Greece at the IOA observatory at the distance of 80 km from the epicenter with a sampling rate of 1 sample/s: (a) 3 h record with strong SES activity in 6.30–7.40 time interval, (b) is the 5 min fragment of (a), showing both electric and magnetic components in expanded time scale [11]. Amplitudes are given in relative units.*

P. Varotsos [11, 13]. The network consists of 10–15 stations. Each station included several (from 6 up to 100) grounded electrical dipoles with the length from 50 m up to 20 km that allows to study spatial characteristics of observed field and separate SES from MT field and noise. In the course of continuous monitoring for more than 35 years, Prof. Varotsos and collaborators identified (as the result of a posteriori analysis) many SES before the following EQs and studied their regularities [11], for example, the selectivity effect: SES can be observed in some sensitive zones and be not observable in vast territories even not far from impending EQ. Prof. Varotsos made a number of correct EQ predictions registered officially before the event. We show interesting case of joint registration SES and horizontal magnetic components recorded on April 19, 1995, 25 days before Grevena-Kozani EQM6.6 on May 13, 1995 (**Figure 2**). Magnetic components look as derivative of electrical impulses that are clearly seen in the lower graph (b) with expanded time scale. In the latter years, Prof. Varotsos' group develops deeper insight in the physics of LE: entropy and natural time analysis for the better understanding of the EQ preparation process and for the distinguishing LE signals from similarly looking variations of MT and noise origin [14, 15].

#### **2. Basic concepts and definitions. Methodology**

#### **2.1 Varying geomagnetic field**

Varying geomagnetic field **B**(*t*) = Bx**ex** + By**ey** + Bz**ez** (where **ex**, **ey**, and **ez** are unit vectors directed to north, east, and downward correspondingly) continuously exists in and around the Earth and is recorded nowadays digitally with a time reading interval *Δt* (1 min or 1 s in our study). All components are functions of time *t* which we skip out for brevity.

#### **2.2 Main sources of observed geomagnetic field**

$$\mathbf{B}(t) = \mathbf{B}\_{\rm MT} + \mathbf{B}\_{\rm noise} + \mathbf{B}\_{\rm LEs} \tag{1}$$

**95**

quake preparation.

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

**B**noise is the ever-present noise, both man-made and natural.

**BLE** is the purely internal field of lithosphere emission, it is usually local and transient, and the ratio of vertical component to the horizontal one usually differs

After the conventional processing using Fourier transform, a **B(***t***)** record of duration *t2−t1* is transformed into a superposition of harmonic components with

Response function is the term widely used in natural sciences and mathematics. In the geoelectromagnetic studies of *electrical conductivity* σ (x, y, z) of the Earth's interior [2–4], the RFs are supposed to be some functions derived from the Earth's electromagnetic (EM) data that provides us with a possibility to determine the conductivity structure of the Earth. EM RFs are usually frequency/(period T) dependent, and then they are complex functions having real (index u) and imagi-

Induction vector C = *A***ex** + *B***ey** (*A* and *B* are determined from the linear equation: Bz = *A*Bx + *B*By). Real induction vectors **Cu** = *Au***ex** + *Bu***ey** possess an important property: in the notation of Wiese used here, they are directed away from a good

Anomalous horizontal magnetic variation tensor [M] is determined from the linear system of equations Bx(**ri**) = MxxBx(**r0**) + MxyBy(**r0**) and

structures between two places (if the source field used is uniform).

By(**ri**) = MyxBx(**r0**) + MyyBy(**r0**), where **r0** and **ri** are coordinates of base (reference) and some other observation place. Tensor [M] reflects the change in geoelectric

The processing of observed geomagnetic field **B**(*t*) for the monitoring of geodynamic and other environmental processes implies transformation of three components of geomagnetic field time series with time reading interval *Δt* (1 min or 1 s in our study) into a variety of time series with temporal resolution *Δτ* (*Δτ*»*Δt*) of different RF components: *Re* and *Im* and *x* and *y* at the set of periods *T1, T2…Tn* of

The theory of geoelectromagnetic methods [2–4] is developed for natural source field in the form of vertically incident plane wave (Tikhonov-Cagniard (T-C) model), which usually holds for an external source field of magnetosphereionosphere origin (named as magnetotelluric field) for the periods less than 104

Ideally RF depends only on the Earth's conductivity distribution which is sensitive to the stress variations and therefore to geodynamic processes including the earth-

s.

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

nary (index v) parts. We use two of these functions.

*2.3.2 Anomalous horizontal magnetic variation tensor*

**2.4 The processing of observed geomagnetic field**

**2.5 The theory of geoelectromagnetic methods**

received harmonics (*Δt* « *Ti* « *Δτ*).

from the same ratio for MT field.

periods *T1, T2…Tn*.

**2.3 Response function**

*2.3.1 Induction vector*

conductor.

where **B**MT = **BMT**ext + **BMT**intn + **BMT**inta is the magnetotelluric field.

**BMT**ext is the external primary magnetic field of the currents in magnetosphere and ionosphere of the Earth.

**BMT**intn is the normal internal secondary magnetic field of the currents induced by **BMT**ext in the Earth's interior having a hypothetical "normal" horizontally layered conductivity structure. The horizontal components of **BMT**intn add together with **BMT**ext increasing observed horizontal MT-field up to doubling over hypothetical ideally conducting Earth. On the contrary, the vertical component of **BMT**intn subtracts from **BMT**ext diminishing observed normal vertical MT field up to 0 (phase neglected).

Thus, **BMT**n = **BMT**ext + **BMT**intn has the horizontal component much greater than the vertical one and embraces great territory equal to external source field dimension.

**BMT**inta is the anomalous internal secondary field arising on local/regional conductivity anomalies as a result of redistribution of the currents responsible for **BMT**intn.

Such subdividing of secondary internal field is rather artificial, but it is used in geoelectromagnetic methods: **BMT**intn in sounding methods, magnetotelluric sounding (MTS) and geomagnetic deep sounding (GDS); **BMT**inta in profiling one, magnetic variation profiling (MVP) [2–5].

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

**B**noise is the ever-present noise, both man-made and natural.

**BLE** is the purely internal field of lithosphere emission, it is usually local and transient, and the ratio of vertical component to the horizontal one usually differs from the same ratio for MT field.

After the conventional processing using Fourier transform, a **B(***t***)** record of duration *t2−t1* is transformed into a superposition of harmonic components with periods *T1, T2…Tn*.

#### **2.3 Response function**

*Seismic Waves - Probing Earth System*

P. Varotsos [11, 13]. The network consists of 10–15 stations. Each station included several (from 6 up to 100) grounded electrical dipoles with the length from 50 m up to 20 km that allows to study spatial characteristics of observed field and separate SES from MT field and noise. In the course of continuous monitoring for more than 35 years, Prof. Varotsos and collaborators identified (as the result of a posteriori analysis) many SES before the following EQs and studied their regularities [11], for example, the selectivity effect: SES can be observed in some sensitive zones and be not observable in vast territories even not far from impending EQ. Prof. Varotsos made a number of correct EQ predictions registered officially before the event. We show interesting case of joint registration SES and horizontal magnetic components recorded on April 19, 1995, 25 days before Grevena-Kozani EQM6.6 on May 13, 1995 (**Figure 2**). Magnetic components look as derivative of electrical impulses that are clearly seen in the lower graph (b) with expanded time scale. In the latter years, Prof. Varotsos' group develops deeper insight in the physics of LE: entropy and natural time analysis for the better understanding of the EQ preparation process and for the distinguishing LE

signals from similarly looking variations of MT and noise origin [14, 15].

Varying geomagnetic field **B**(*t*) = Bx**ex** + By**ey** + Bz**ez** (where **ex**, **ey**, and **ez** are unit vectors directed to north, east, and downward correspondingly) continuously exists in and around the Earth and is recorded nowadays digitally with a time reading interval *Δt* (1 min or 1 s in our study). All components are functions of time *t*

**B**(*t*) = **B**MT + **B**noise + **B**LE, (1)

**BMT**ext is the external primary magnetic field of the currents in magnetosphere

where **B**MT = **BMT**ext + **BMT**intn + **BMT**inta is the magnetotelluric field.

**BMT**intn is the normal internal secondary magnetic field of the currents induced by **BMT**ext in the Earth's interior having a hypothetical "normal" horizontally layered conductivity structure. The horizontal components of **BMT**intn add together with **BMT**ext increasing observed horizontal MT-field up to doubling over hypothetical ideally conducting Earth. On the contrary, the vertical component of **BMT**intn subtracts from **BMT**ext diminishing observed normal vertical MT field up

Thus, **BMT**n = **BMT**ext + **BMT**intn has the horizontal component much greater than the vertical one and embraces great territory equal to external source field

**BMT**inta is the anomalous internal secondary field arising on local/regional conductivity anomalies as a result of redistribution of the currents responsible for

Such subdividing of secondary internal field is rather artificial, but it is used in geoelectromagnetic methods: **BMT**intn in sounding methods, magnetotelluric sounding (MTS) and geomagnetic deep sounding (GDS); **BMT**inta in profiling one,

**2. Basic concepts and definitions. Methodology**

**2.2 Main sources of observed geomagnetic field**

**2.1 Varying geomagnetic field**

which we skip out for brevity.

and ionosphere of the Earth.

to 0 (phase neglected).

magnetic variation profiling (MVP) [2–5].

dimension.

**BMT**intn.

**94**

Response function is the term widely used in natural sciences and mathematics. In the geoelectromagnetic studies of *electrical conductivity* σ (x, y, z) of the Earth's interior [2–4], the RFs are supposed to be some functions derived from the Earth's electromagnetic (EM) data that provides us with a possibility to determine the conductivity structure of the Earth. EM RFs are usually frequency/(period T) dependent, and then they are complex functions having real (index u) and imaginary (index v) parts. We use two of these functions.

#### *2.3.1 Induction vector*

Induction vector C = *A***ex** + *B***ey** (*A* and *B* are determined from the linear equation: Bz = *A*Bx + *B*By). Real induction vectors **Cu** = *Au***ex** + *Bu***ey** possess an important property: in the notation of Wiese used here, they are directed away from a good conductor.

#### *2.3.2 Anomalous horizontal magnetic variation tensor*

Anomalous horizontal magnetic variation tensor [M] is determined from the linear system of equations Bx(**ri**) = MxxBx(**r0**) + MxyBy(**r0**) and By(**ri**) = MyxBx(**r0**) + MyyBy(**r0**), where **r0** and **ri** are coordinates of base (reference) and some other observation place. Tensor [M] reflects the change in geoelectric structures between two places (if the source field used is uniform).

#### **2.4 The processing of observed geomagnetic field**

The processing of observed geomagnetic field **B**(*t*) for the monitoring of geodynamic and other environmental processes implies transformation of three components of geomagnetic field time series with time reading interval *Δt* (1 min or 1 s in our study) into a variety of time series with temporal resolution *Δτ* (*Δτ*»*Δt*) of different RF components: *Re* and *Im* and *x* and *y* at the set of periods *T1, T2…Tn* of received harmonics (*Δt* « *Ti* « *Δτ*).

#### **2.5 The theory of geoelectromagnetic methods**

The theory of geoelectromagnetic methods [2–4] is developed for natural source field in the form of vertically incident plane wave (Tikhonov-Cagniard (T-C) model), which usually holds for an external source field of magnetosphereionosphere origin (named as magnetotelluric field) for the periods less than 104 s. Ideally RF depends only on the Earth's conductivity distribution which is sensitive to the stress variations and therefore to geodynamic processes including the earthquake preparation.

#### **3. Variations of geomagnetic response functions (mainly induction vector) before the 2011 Tohoku earthquake**

RFs and their variations, especially in relation with EQs preparation, were studied in Japan for many years and were described in many works among which we cite only few [16–18]. In the last two decades, the RF approach became less used for EQ studies because of strong noise at Japanese observatories. After the catastrophic Tohoku EQ on March 11, 2011, near Japan, we analyzed the available geomagnetic data to obtain some EQ precursors using the RF method. Some results were presented in Russian [19–21], which together with the latest results of our study will be summarized below.

**Data used**: We obtained data of 17 Japanese geomagnetic observatories (**Figure 3**, **Table 1**) for time interval of 12–20 years with temporal reading every 1 min (and few observatories with 1 s reading). For the conversion of geomagnetic field **B** time series into RF time series, we used the advanced multi-window remote reference (rr) robust programs with coherency control [22, 23]. After processing we got values of four components of induction vector *Au*, *Bu*, *Av*, *Bv* for each day for five period intervals centered at: 225, 450, 900, 1800, and 3600 s. To reduce the great scattering, everyday values were smoothed with moving windows and/or were found average or median values for some interval (usually 1 month).

#### **3.1 Results of processing for separation of middle-term precursors**

Analyzing large material of processed data for 15 years from 2001 till 2015, we found that aperiodic variations (or enhancement of annual variation) of induction vectors were observed at periods 225, 450, and 900 s during 3–5 years before the Tohoku EQ at stations: HAR, KAK, OTA, KNZ, and TTK, most clearly at period 450 s presented in **Figure 4**. We should emphasize that no such aperiodic variations were observed at other stations including ESA and MIZ, which are the nearest to the EQ epicenter. The best correlation of middle-term anomalies is observed between the two most remote (620 km) from each other stations HAR and TTK: at both we see strong synchronous variations of induction vectors with maxima in the end of 2008, the end of 2009, with several maxima in 2010, in the beginning of 2011, and

#### **Figure 3.**

*Map of Japan with real Cu and imaginary Cv induction vectors for the period 450 s at 17 geomagnetic observatories by 1 min record data. (a) Mean vectors for the year 2001. Stars present EQs with M > 7.8 since 2001. Elements of plate tectonics; white arrows represent the directions of plate motions; E. P., Eurasian plate; P. P., Pacific plate; P. S. P., Philippine Sea plate; S. T., Sagami trough; dotted line, volcanic front. (b) Mean vectors for 2011. Circles present EQs with M* ≥ *7. The depth of hypocenters is less than 50 km for all EQs.*

**97**

**Table 1.**

appeared in 2011.

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

**Code Station name Geom. lat. Geom. long. Geogr. lat. Geogr. long. Processed years** MMB Memambetsu 35.44 148.24 43.910 144.189 1993–2012 AKA Akaigawa 34.31 151.09 43.072 140.815 2001–2012 YOK Yokohama 32.28 150.43 40.993 141.240 2001–2012 ESA Esashi 30.55 150.09 39.237 141.355 1997–2012 MIZ Mizusawa 30.41 150.21 39.112 141.204 1997–2015 HAR Haramachi 28.90 150.25 37.615 140.953 2001–2015 SIK Shika 28.04 153.96 37.082 136.773 2001–2012 KAK Kakioka 27.47 150.78 36.232 140.186 1956–2015 HAG Hagiwara 26.98 153.47 35.985 137.186 2001–2012 OTA Otaki 26.54 150.63 35.292 140.230 2001–2015 KNZ Kanozan 26.48 150.87 35.256 139.956 1996–2016 YOS Yoshiwa 25.12 157.87 34.476 132.176 2001–2012 TTK Totsukawa 24.83 154.52 33.932 135.802 2001–2015 HTY Hatizyo 24.30 150.75 33.073 139.825 1991–2008 MUR Muroto 24.10 155.99 33.319 134.122 2004–2012 KUJ Kuju 23.65 158.58 33.061 131.260 2001–2015 KNY Kanoya 22.00 158.80 31.424 130.88 1991–2016

return to the previous level after the Tohoku EQ. We may suppose that these aperiodic variations can be the middle-term precursors of the Tohoku EQ. These observatories are located not at the shortest distance from the EQ, which is in agreement with well-known phenomenon of spatial selectivity of EQ precursors known during the centuries for hydrological precursors and recently proven for LE registered in

Having 1 min time series, we can analyze only geomagnetic variations with period T > 3 min, and the most interesting shorter part of ULF spectra (0.01– 10 Hz), where strongest **BLE** have been observed [7–9], is left not resolved. So, we get 1 s data for observatories KAK, KNZ, ESA, MIZ, and for short time intervals for

Processing of records from 18 observatories (16 of them are shown in **Figure 3** and KYS and UCU in **Figure 5**) for the determination of horizontal tensors [M] with KAK as the base station yields the absence of noticeable horizontal tensor anomalies in ESA, MIZ, HAR, TTK, and MUR but reveals their existence in KNZ, UCU, OTA, and KYS (**Figure 4a**). In KNZ and OTA the enhancement of real tensor components Mxx and Myy equals to ≈40% and ≈30% correspondingly at periods T < 500 s decreasing at longer periods. This result was supported by direct visual measurements described below. At closely located observatories KNZ and OTA, the latitudinal (E-W) component of induction vector at period 450 s and shorter increased (in 2011 comparatively to 2001) in opposite directions: westward in KNZ and eastward in OTA (see **Figure 3b**). It means that between these two observatories, an additional current (of geodynamic origin)

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

the form of seismic electric signal [11, 13].

*Geomagnetic observatories in Japan used in the study.*

UCU and KYS to analyze RF for periods T > 5 s.

**3.2 Boso conductivity anomaly**


*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

**Table 1.**

*Seismic Waves - Probing Earth System*

summarized below.

**3. Variations of geomagnetic response functions (mainly induction** 

RFs and their variations, especially in relation with EQs preparation, were studied in Japan for many years and were described in many works among which we cite only few [16–18]. In the last two decades, the RF approach became less used for EQ studies because of strong noise at Japanese observatories. After the catastrophic Tohoku EQ on March 11, 2011, near Japan, we analyzed the available geomagnetic data to obtain some EQ precursors using the RF method. Some results were presented in Russian [19–21], which together with the latest results of our study will be

**Data used**: We obtained data of 17 Japanese geomagnetic observatories (**Figure 3**, **Table 1**) for time interval of 12–20 years with temporal reading every 1 min (and few observatories with 1 s reading). For the conversion of geomagnetic field **B** time series into RF time series, we used the advanced multi-window remote reference (rr) robust programs with coherency control [22, 23]. After processing we got values of four components of induction vector *Au*, *Bu*, *Av*, *Bv* for each day for five period intervals centered at: 225, 450, 900, 1800, and 3600 s. To reduce the great scattering, everyday values were smoothed with moving windows and/or were

found average or median values for some interval (usually 1 month).

**3.1 Results of processing for separation of middle-term precursors**

Analyzing large material of processed data for 15 years from 2001 till 2015, we found that aperiodic variations (or enhancement of annual variation) of induction vectors were observed at periods 225, 450, and 900 s during 3–5 years before the Tohoku EQ at stations: HAR, KAK, OTA, KNZ, and TTK, most clearly at period 450 s presented in **Figure 4**. We should emphasize that no such aperiodic variations were observed at other stations including ESA and MIZ, which are the nearest to the EQ epicenter. The best correlation of middle-term anomalies is observed between the two most remote (620 km) from each other stations HAR and TTK: at both we see strong synchronous variations of induction vectors with maxima in the end of 2008, the end of 2009, with several maxima in 2010, in the beginning of 2011, and

*Map of Japan with real Cu and imaginary Cv induction vectors for the period 450 s at 17 geomagnetic observatories by 1 min record data. (a) Mean vectors for the year 2001. Stars present EQs with M > 7.8 since 2001. Elements of plate tectonics; white arrows represent the directions of plate motions; E. P., Eurasian plate; P. P., Pacific plate; P. S. P., Philippine Sea plate; S. T., Sagami trough; dotted line, volcanic front. (b) Mean vectors for 2011. Circles present EQs with M* ≥ *7. The depth of hypocenters is less than 50 km for all EQs.*

**vector) before the 2011 Tohoku earthquake**

**96**

**Figure 3.**

*Geomagnetic observatories in Japan used in the study.*

return to the previous level after the Tohoku EQ. We may suppose that these aperiodic variations can be the middle-term precursors of the Tohoku EQ. These observatories are located not at the shortest distance from the EQ, which is in agreement with well-known phenomenon of spatial selectivity of EQ precursors known during the centuries for hydrological precursors and recently proven for LE registered in the form of seismic electric signal [11, 13].

Having 1 min time series, we can analyze only geomagnetic variations with period T > 3 min, and the most interesting shorter part of ULF spectra (0.01– 10 Hz), where strongest **BLE** have been observed [7–9], is left not resolved. So, we get 1 s data for observatories KAK, KNZ, ESA, MIZ, and for short time intervals for UCU and KYS to analyze RF for periods T > 5 s.

#### **3.2 Boso conductivity anomaly**

Processing of records from 18 observatories (16 of them are shown in **Figure 3** and KYS and UCU in **Figure 5**) for the determination of horizontal tensors [M] with KAK as the base station yields the absence of noticeable horizontal tensor anomalies in ESA, MIZ, HAR, TTK, and MUR but reveals their existence in KNZ, UCU, OTA, and KYS (**Figure 4a**). In KNZ and OTA the enhancement of real tensor components Mxx and Myy equals to ≈40% and ≈30% correspondingly at periods T < 500 s decreasing at longer periods. This result was supported by direct visual measurements described below. At closely located observatories KNZ and OTA, the latitudinal (E-W) component of induction vector at period 450 s and shorter increased (in 2011 comparatively to 2001) in opposite directions: westward in KNZ and eastward in OTA (see **Figure 3b**). It means that between these two observatories, an additional current (of geodynamic origin) appeared in 2011.

#### **Figure 4.**

*Variations of the monthly mean induction vector components at the period of 450 s during 2001–2015 at five observatories with significant changes before the Tohoku EQ: HAR, KAK, OTA, KNZ, and TTK. Vertical bars present the uncertainty of every monthly mean value. Two strong EQs are shown by vertical lines.*

#### *3.2.1 Visual analysis of geomagnetic records*

Considering the geomagnetic field synchronous records (**Figure 3a**), we noticed that magnetotelluric field appears synchronously at all observatories, while noise appears locally at each one. The stations most contaminated by noise are UCU and KNZ which are the nearest to DC railways. But during the after-midnight time interval from ≈1:30 to ≈4:30 LT (16:30–19:30 UT) the strong noise from DC railways almost disappears.

Direct measurements of the strong MT amplitude variations in each component provide a check (not precise but very reliable) of the results obtained by processing. So, the enhancement of Bx at KNZ and OTA at approximately 30–40% exists, and it can be interpreted only by the electrical conductivity anomaly under the observatories, i.e. under the central part of the Boso peninsula.

#### **3.3 Comparison with geology and tectonic evidence**

The relation between Mxx and Myy anomalies in KNZ defines WNW-ESE strike of the Boso conductivity anomaly. Geological data [25, 26] presented in **Figure 4b**–**c**

**99**

**Figure 5.**

*started on February 22, 2011.*

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

suggest the existence of anomalous conductor of WNW-ESE strike in Miura Group sediments of the Kanto plain at depth 0–4 km. Relations between Mxx and Myy in UCU, OTA, and KYS are different as seen in **Figure 6a**. It means that the direction of anomalous currents is also different under each observatory. Calculations show that at least 50% of anomalous currents should be located near the surface in the sedi-

*(a) Synchronous records (1 min data) of 10 Japanese and 1 Kamchatka (PET) geomagnetic observatories 2 days before the Tohoku earthquake. In the UCU and KNZ observatories records, we see during daytime strong noise due to DC electric trains and an absence of this noise during the hours after midnight. Geomagnetic activity presented by global 3 h index Кp was as follows: in the 6–9 UT hours time interval* K*p = 1+; in 9–12 UT hours,* K*p = 1–; in 12–15 UT hours,* K*p = 1; in 15–18 UT hours,* K*p = 1–; in 18–21 UT hours,* K*p = 1 + . (b) Synchronous record (February 24, 2011) (1 s data) of eight Japanese observatories 80 min after midnight (15 h UT). Magnetic activity was very low: Kp =0+. DC railway traffic is almost stopped, but the noise-like variations were not terminated in the Boso peninsula. Maybe it is a precursory LE which according to [24]* 

On the other hand, the plate tectonic evidences that the Boso anomaly is located over the Sagami trough, structure at the depth 15–20 km in the complex junction of three lithosphere plates (**Figure 3a**). Strike of the trough is the same, WNW-ESE, so

The eastern part of both conductors (shallow sediments and deep trough) has contact with seawater, while the western one can contact with a magma reservoir. In such a circuit it can be some unstable area(s) with conductivity strongly dependent

some part of the anomalous conductor can be located in the Sagami trough.

ments of the Kanto plain to fit the received data.

on stress and sensitive to stress changes related with EQs.

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

#### **Figure 5.**

*Seismic Waves - Probing Earth System*

*3.2.1 Visual analysis of geomagnetic records*

ries, i.e. under the central part of the Boso peninsula.

**3.3 Comparison with geology and tectonic evidence**

railways almost disappears.

Considering the geomagnetic field synchronous records (**Figure 3a**), we noticed that magnetotelluric field appears synchronously at all observatories, while noise appears locally at each one. The stations most contaminated by noise are UCU and KNZ which are the nearest to DC railways. But during the after-midnight time interval from ≈1:30 to ≈4:30 LT (16:30–19:30 UT) the strong noise from DC

*Variations of the monthly mean induction vector components at the period of 450 s during 2001–2015 at five observatories with significant changes before the Tohoku EQ: HAR, KAK, OTA, KNZ, and TTK. Vertical bars* 

*present the uncertainty of every monthly mean value. Two strong EQs are shown by vertical lines.*

Direct measurements of the strong MT amplitude variations in each component provide a check (not precise but very reliable) of the results obtained by processing. So, the enhancement of Bx at KNZ and OTA at approximately 30–40% exists, and it can be interpreted only by the electrical conductivity anomaly under the observato-

The relation between Mxx and Myy anomalies in KNZ defines WNW-ESE strike of the Boso conductivity anomaly. Geological data [25, 26] presented in **Figure 4b**–**c**

**98**

**Figure 4.**

*(a) Synchronous records (1 min data) of 10 Japanese and 1 Kamchatka (PET) geomagnetic observatories 2 days before the Tohoku earthquake. In the UCU and KNZ observatories records, we see during daytime strong noise due to DC electric trains and an absence of this noise during the hours after midnight. Geomagnetic activity presented by global 3 h index Кp was as follows: in the 6–9 UT hours time interval* K*p = 1+; in 9–12 UT hours,* K*p = 1–; in 12–15 UT hours,* K*p = 1; in 15–18 UT hours,* K*p = 1–; in 18–21 UT hours,* K*p = 1 + . (b) Synchronous record (February 24, 2011) (1 s data) of eight Japanese observatories 80 min after midnight (15 h UT). Magnetic activity was very low: Kp =0+. DC railway traffic is almost stopped, but the noise-like variations were not terminated in the Boso peninsula. Maybe it is a precursory LE which according to [24] started on February 22, 2011.*

suggest the existence of anomalous conductor of WNW-ESE strike in Miura Group sediments of the Kanto plain at depth 0–4 km. Relations between Mxx and Myy in UCU, OTA, and KYS are different as seen in **Figure 6a**. It means that the direction of anomalous currents is also different under each observatory. Calculations show that at least 50% of anomalous currents should be located near the surface in the sediments of the Kanto plain to fit the received data.

On the other hand, the plate tectonic evidences that the Boso anomaly is located over the Sagami trough, structure at the depth 15–20 km in the complex junction of three lithosphere plates (**Figure 3a**). Strike of the trough is the same, WNW-ESE, so some part of the anomalous conductor can be located in the Sagami trough.

The eastern part of both conductors (shallow sediments and deep trough) has contact with seawater, while the western one can contact with a magma reservoir. In such a circuit it can be some unstable area(s) with conductivity strongly dependent on stress and sensitive to stress changes related with EQs.

In **Figure 6b**, vectors are shown for a period of about an hour (4000 s), at which industrial noise is practically absent and vectors adequately reflect the heterogeneity of geoelectric structure. In **Figure 6c**, vectors at the period 25 s are built with dominated noise field, which is greater than MT field on four observatories considered. Real and imaginary vectors at periods 16, 25, 50, and partly at 200 s (**Figure 6d**) are directed to the source of noises—the nearest railway. To reduce influence of the noise, night records and remote reference technique were used (**Figure 6f**). Received corrected vectors appeared still very scattered (**Figure 6e**) and for monitoring of geodynamic processes can be used cautiously. However, vectors averaged over a long period of time can be used for clarifying of the geoelectric structure. Corrected real vector in KNZ at the shortest periods directs to north.

#### **Figure 6.**

*RFs and Neogene sediments in the Kanto plain and the Boso peninsula. (a) Frequency characteristics of the modulus of horizontal tensor [M] main components at Boso observatories with reference to the base observatory KAK. Every curve is a mean value for 7 years (KNZ), 25 days (UCU), 1 year (OTA), and 12 days (KYS). Interval of averaging (aver.) with the date and the length of processed realizations (Proc.) is written at every graph (they were chosen depending on the interval of available data and their discreteness). (b) Thickness of Neogene sediments [25, 26] and induction vectors for period* ≈*1 h, named observatories with real and imaginary vectors—is our processing, the other six real vectors are taken from [16]. (c) Thickness of Miura group deposits with "N.8 half graben fills" and induction vectors for T = 25 s obtained from the dominant DC noise and directed to the noise source—DC railways given by thin lines for suburb railways and by thick line for magistral one. (d) Similar results for another four periods. (e) Results of the same data processing with an attempt to make away the impact of the noise by means of either only after-midnight 4 h use or by remote reference technique application. (f) Frequency characteristics of induction vector components at KNZ. Dark lines for the wide period range are the results of ss (single station) processing of 3-day realizations with sliding reference to middle day; light lines, processing of after-midnight 4 h records of the same 20 days from February 18 to March 9, 2011.*

**101**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

It means that the most conductive part of Boso electrical conductivity anomaly is located to south of KNZ, apparently near the southern side of the asymmetric "N.8

Results of the single station and nighttime records processing at KNZ are given in **Figure 6f**. We see that full-day and nighttime results significantly differ from each other only for *Bu* and partly *Bv* components because a railway is located to the west from KNZ and brings the distortions mainly in the eastern component. The northern component is less affected by noise at periods 100 s and more that opens the possibility to use it for separation of EQ precursor that will be used in the next section.

The induction vector derived from very noisy records, practically from noise field, has small stable phase. Therefore, if some other magnetic fields, which are usually not so stable (let it be a precursor field), are superimposed on the field of noise, exactly the phase of induction vector will be the most sensitive component

Below we apply a new approach developed by Tregubenko [27], who used it for processing the data of seismo-prognosis monitoring network in Ukraine. He separated precursors before few strongest (M ≈ 4) Crimean EQs occurred during 15 years, in particular before the Sudak, Crimea EQM3.9 on January 24, 2005 [27]. We applied this approach to KNZ, KAK, and ESA 1-s data, but the precursor was found only in KNZ. We can explain this by the spatial selectivity of the precursors: high sensitivity of KNZ place is quite natural in virtue of Boso electrical conductiv-

The processing was made with the use of Varentsov's [22] program. Coherences

**Step 1.** A 7-year-long (2005–2011) geomagnetic field time series with every 1 s reading was processed for every month as a single unit. Arg(*A*) time series with every month reading were received as in **Figure 7a** and analyzed by a polynomial approximation approach. The most significant first-, second-, and seventh (quasiannual)-order polynomials were extracted from the rough data, and we obtained **Figure 7b** which is more perspective for comparison with EQs. But 1-month temporal resolution of RF is not sufficient for such an analysis. As for the Tohoku EQ precursors, we see a 9-month-long negative anomaly in 2010 approximately

**Step 2**. A 2-year-long (2010–2011) 1 s time series were processed for every day as single unit. Large scatter of everyday results was reduced by averaging with moving window of 5 days long with 1-day shift. From these curves, i.e., arg(*A*) time series with everyday reading, we extracted first-, second-, and seventh (quasi-annual) order polynomials determined in step 1. The result is shown by the gray rough curve

were used as weight estimates for averaging the results. To minimize the effect of noise, the estimates with multiple coherences less than 0.7 were ignored that allowed us to obtain minimally shifted estimates of induction vector's components. Maximum anomalous effect before the Tohoku EQ was observed for the phase of the induction vector northern component—arg(*A*) for periods 100–200 s. For the longer periods, the anomaly gradually decreases, so that we now present the results

for T = 100 s. The processing and analysis were made in two steps:

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

**4. Short-term precursor separation**

ity anomaly located just under KNZ observatory.

**4.1 Introductory remarks**

for a precursor separation.

**4.2 Processing of KNZ data**

1 year before the main event.

half graben fills" of the Miura Group sediments [26].

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

It means that the most conductive part of Boso electrical conductivity anomaly is located to south of KNZ, apparently near the southern side of the asymmetric "N.8 half graben fills" of the Miura Group sediments [26].

Results of the single station and nighttime records processing at KNZ are given in **Figure 6f**. We see that full-day and nighttime results significantly differ from each other only for *Bu* and partly *Bv* components because a railway is located to the west from KNZ and brings the distortions mainly in the eastern component. The northern component is less affected by noise at periods 100 s and more that opens the possibility to use it for separation of EQ precursor that will be used in the next section.

#### **4. Short-term precursor separation**

#### **4.1 Introductory remarks**

*Seismic Waves - Probing Earth System*

In **Figure 6b**, vectors are shown for a period of about an hour (4000 s), at which

industrial noise is practically absent and vectors adequately reflect the heterogeneity of geoelectric structure. In **Figure 6c**, vectors at the period 25 s are built with dominated noise field, which is greater than MT field on four observatories considered. Real and imaginary vectors at periods 16, 25, 50, and partly at 200 s (**Figure 6d**) are directed to the source of noises—the nearest railway. To reduce influence of the noise, night records and remote reference technique were used (**Figure 6f**). Received corrected vectors appeared still very scattered (**Figure 6e**) and for monitoring of geodynamic processes can be used cautiously. However, vectors averaged over a long period of time can be used for clarifying of the geoelectric structure. Corrected real vector in KNZ at the shortest periods directs to north.

*RFs and Neogene sediments in the Kanto plain and the Boso peninsula. (a) Frequency characteristics of the modulus of horizontal tensor [M] main components at Boso observatories with reference to the base observatory KAK. Every curve is a mean value for 7 years (KNZ), 25 days (UCU), 1 year (OTA), and 12 days (KYS). Interval of averaging (aver.) with the date and the length of processed realizations (Proc.) is written at every graph (they were chosen depending on the interval of available data and their discreteness). (b) Thickness of Neogene sediments [25, 26] and induction vectors for period* ≈*1 h, named observatories with real and imaginary vectors—is our processing, the other six real vectors are taken from [16]. (c) Thickness of Miura group deposits with "N.8 half graben fills" and induction vectors for T = 25 s obtained from the dominant DC noise and directed to the noise source—DC railways given by thin lines for suburb railways and by thick line for magistral one. (d) Similar results for another four periods. (e) Results of the same data processing with an attempt to make away the impact of the noise by means of either only after-midnight 4 h use or by remote reference technique application. (f) Frequency characteristics of induction vector components at KNZ. Dark lines for the wide period range are the results of ss (single station) processing of 3-day realizations with sliding reference to middle day; light lines, processing of after-midnight 4 h records of the same 20 days from February 18 to March 9, 2011.*

**100**

**Figure 6.**

The induction vector derived from very noisy records, practically from noise field, has small stable phase. Therefore, if some other magnetic fields, which are usually not so stable (let it be a precursor field), are superimposed on the field of noise, exactly the phase of induction vector will be the most sensitive component for a precursor separation.

Below we apply a new approach developed by Tregubenko [27], who used it for processing the data of seismo-prognosis monitoring network in Ukraine. He separated precursors before few strongest (M ≈ 4) Crimean EQs occurred during 15 years, in particular before the Sudak, Crimea EQM3.9 on January 24, 2005 [27]. We applied this approach to KNZ, KAK, and ESA 1-s data, but the precursor was found only in KNZ. We can explain this by the spatial selectivity of the precursors: high sensitivity of KNZ place is quite natural in virtue of Boso electrical conductivity anomaly located just under KNZ observatory.

#### **4.2 Processing of KNZ data**

The processing was made with the use of Varentsov's [22] program. Coherences were used as weight estimates for averaging the results. To minimize the effect of noise, the estimates with multiple coherences less than 0.7 were ignored that allowed us to obtain minimally shifted estimates of induction vector's components. Maximum anomalous effect before the Tohoku EQ was observed for the phase of the induction vector northern component—arg(*A*) for periods 100–200 s. For the longer periods, the anomaly gradually decreases, so that we now present the results for T = 100 s. The processing and analysis were made in two steps:

**Step 1.** A 7-year-long (2005–2011) geomagnetic field time series with every 1 s reading was processed for every month as a single unit. Arg(*A*) time series with every month reading were received as in **Figure 7a** and analyzed by a polynomial approximation approach. The most significant first-, second-, and seventh (quasiannual)-order polynomials were extracted from the rough data, and we obtained **Figure 7b** which is more perspective for comparison with EQs. But 1-month temporal resolution of RF is not sufficient for such an analysis. As for the Tohoku EQ precursors, we see a 9-month-long negative anomaly in 2010 approximately 1 year before the main event.

**Step 2**. A 2-year-long (2010–2011) 1 s time series were processed for every day as single unit. Large scatter of everyday results was reduced by averaging with moving window of 5 days long with 1-day shift. From these curves, i.e., arg(*A*) time series with everyday reading, we extracted first-, second-, and seventh (quasi-annual) order polynomials determined in step 1. The result is shown by the gray rough curve

#### **Figure 7.**

*Variations of arg(*A*) for the period T = 100 s at the observatory KNZ during 2005–2011. (a) Monthly values of arg(*A*) are given by dots. The dashed straight line and bold solid line are the first- and second-order polynomials, respectively. Thin smooth line is quasi-annual variations obtained as seventh-order polynomial approximation. In the upper left corner, the determination of mean annual variation is shown (first- and second-order polynomials were excluded). (b) Variations of arg(*A*) after removal of the first-, second-, and seventh (quasi-annual)-order polynomials. Moments of strong EQsM > 5 are indicated by vertical lines with given magnitude M (the first number in parentheses is the depth of the hypocenter, and the second one is distance from epicenters to the observatory KNZ, both are given in km).*

in **Figure 8a**. The bold solid line is the result of averaging with moving window of 29 days with 1-day shift to suppress monthly variations arising from the Moon rotation around the Earth (gravity effect) and the Sun rotation around its axis (magnetic activity effect). The mean for 7 years 2005–2011 annual variation have been subtracted, but we see a residual annual variation in **Figure 8a** (RF annual variation enhancement was recorded at several observatories 2–3 years before Tohoku EQ and can be considered as middle-term precursor). So, such a residual annual variation was determined once more from 2-year data presented in **Figure 8a** and subtracted; the result is presented in **Figure 8b**.

#### **4.3 Discussion of short term precursor**

The variations of arg(*A*) given by the bold solid line in **Figure 8b** are cleaned from periodic variations of annual and monthly periods, which make it more convenient to identify EQ precursors. Indeed, we see a strong bay-like variation that begins almost 2 months before the Tohoku EQ and has approximately 2-month duration. This is in good agreement with the finding of Prof. Varotsos' team [14, 15]. In particular, Varotsos et al. showed that the initiation of an SES activity in Japan appears almost simultaneously with the minimum of the fluctuations of the order parameter of seismicity analyzed in natural time, and such a minimum was clearly observed [15] on January 5, 2011, that is, almost 2 months before the Tohoku EQ occurrence.

Time of beginning of a bay-like precursory variation and its duration depends on the magnitude of an expected EQ. This time is equal to approximately 2 weeks for the processed Crimean EQs with magnitude approximately 4 [27] and 2 months for Tohoku EQ with magnitude 9 according to our study.

**103**

**Figure 8.**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

Kopytenko et al. [24] compared nighttime records of KAK and UCU observatories (see **Figures 3**, **6**) in frequency range of 0.33–0.01 Hz for the interval of 21 days before the Tohoku EQ, that is, since February 2, 2011 till March 3, 2011. They found the appearance of anomalous changes on February 22, 2011 (18 days before EQ ): decrease of the correlation coefficients between geomagnetic components of KAK and UCU observatories and rise of Bz component in sub-diapason 0.033–0.01 Hz. It

*Variations of arg(*A*) for the period T = 100 s at the observatory KNZ by the data for 2010–2011 years. (a) Rough gray curve is the result of everyday processing after moving averaging with window length of 5 days with 1-day shift. Bold solid line is the result of averaging with moving window of 29 days (for elimination of monthly variation) with 1-day shift. (The first -, second-, and seventh (quasi-annual)-order polynomials determined from seven years data and presented in Figure 7a were subtracted). The time of the Tohoku EQ on 11.03.2011 is marked by a vertical arrow. (b) The same after the removal of residual annual variation* 

Now let us see **Figure 5b**. It presents nighttime records on February 24, 2011, 16 days before the Tohoku EQ, in geomagnetically quite interval with rather good temporal and amplitude resolution. MT variations in the horizontal components are almost the same at all presented observatories distributed at the territory 2000 km long. In the records of UCU and KNZ (separated by 17 km) we see strong varitations with frequencies of 0.002–0.1 Hz and amplitude of 0.2 and 0.5 nT, respectively, and even more strong variations in Bz component. All of this is in good agreement with the results of [24]. Variations in KNZ and UCU cover approximately the same frequency diapason as in [24], slightly correlate one with the other, and are not observed at other observatories. All signs of LE! But we cannot exclude that there are some remainders of the daytime noise from DC traffic. We need several more observatories (as SES network in Greece) for more definite conclusions.

To use the LE for EQ prediction, one needs to know its lead time, amplitude, frequency characteristic, and expected distribution of sensitive places in the Earth

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

was interpreted as appearance LE.

*determined from 2010-2011 data and given in Figure 8(a) by thin line.*

**5. Discussion of LE features**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

#### **Figure 8.**

*Seismic Waves - Probing Earth System*

the result is presented in **Figure 8b**.

**4.3 Discussion of short term precursor**

*distance from epicenters to the observatory KNZ, both are given in km).*

in **Figure 8a**. The bold solid line is the result of averaging with moving window of 29 days with 1-day shift to suppress monthly variations arising from the Moon rotation around the Earth (gravity effect) and the Sun rotation around its axis (magnetic activity effect). The mean for 7 years 2005–2011 annual variation have been subtracted, but we see a residual annual variation in **Figure 8a** (RF annual variation enhancement was recorded at several observatories 2–3 years before Tohoku EQ and can be considered as middle-term precursor). So, such a residual annual variation was determined once more from 2-year data presented in **Figure 8a** and subtracted;

*Variations of arg(*A*) for the period T = 100 s at the observatory KNZ during 2005–2011. (a) Monthly values of arg(*A*) are given by dots. The dashed straight line and bold solid line are the first- and second-order polynomials, respectively. Thin smooth line is quasi-annual variations obtained as seventh-order polynomial approximation. In the upper left corner, the determination of mean annual variation is shown (first- and second-order polynomials were excluded). (b) Variations of arg(*A*) after removal of the first-, second-, and seventh (quasi-annual)-order polynomials. Moments of strong EQsM > 5 are indicated by vertical lines with given magnitude M (the first number in parentheses is the depth of the hypocenter, and the second one is* 

The variations of arg(*A*) given by the bold solid line in **Figure 8b** are cleaned from periodic variations of annual and monthly periods, which make it more convenient to identify EQ precursors. Indeed, we see a strong bay-like variation that begins almost 2 months before the Tohoku EQ and has approximately 2-month

[14, 15]. In particular, Varotsos et al. showed that the initiation of an SES activity in Japan appears almost simultaneously with the minimum of the fluctuations of the order parameter of seismicity analyzed in natural time, and such a minimum was clearly observed [15] on January 5, 2011, that is, almost 2 months before the Tohoku

Time of beginning of a bay-like precursory variation and its duration depends on the magnitude of an expected EQ. This time is equal to approximately 2 weeks for the processed Crimean EQs with magnitude approximately 4 [27] and 2 months

duration. This is in good agreement with the finding of Prof. Varotsos' team

for Tohoku EQ with magnitude 9 according to our study.

**102**

EQ occurrence.

**Figure 7.**

*Variations of arg(*A*) for the period T = 100 s at the observatory KNZ by the data for 2010–2011 years. (a) Rough gray curve is the result of everyday processing after moving averaging with window length of 5 days with 1-day shift. Bold solid line is the result of averaging with moving window of 29 days (for elimination of monthly variation) with 1-day shift. (The first -, second-, and seventh (quasi-annual)-order polynomials determined from seven years data and presented in Figure 7a were subtracted). The time of the Tohoku EQ on 11.03.2011 is marked by a vertical arrow. (b) The same after the removal of residual annual variation determined from 2010-2011 data and given in Figure 8(a) by thin line.*

Kopytenko et al. [24] compared nighttime records of KAK and UCU observatories (see **Figures 3**, **6**) in frequency range of 0.33–0.01 Hz for the interval of 21 days before the Tohoku EQ, that is, since February 2, 2011 till March 3, 2011. They found the appearance of anomalous changes on February 22, 2011 (18 days before EQ ): decrease of the correlation coefficients between geomagnetic components of KAK and UCU observatories and rise of Bz component in sub-diapason 0.033–0.01 Hz. It was interpreted as appearance LE.

Now let us see **Figure 5b**. It presents nighttime records on February 24, 2011, 16 days before the Tohoku EQ, in geomagnetically quite interval with rather good temporal and amplitude resolution. MT variations in the horizontal components are almost the same at all presented observatories distributed at the territory 2000 km long. In the records of UCU and KNZ (separated by 17 km) we see strong varitations with frequencies of 0.002–0.1 Hz and amplitude of 0.2 and 0.5 nT, respectively, and even more strong variations in Bz component. All of this is in good agreement with the results of [24]. Variations in KNZ and UCU cover approximately the same frequency diapason as in [24], slightly correlate one with the other, and are not observed at other observatories. All signs of LE! But we cannot exclude that there are some remainders of the daytime noise from DC traffic. We need several more observatories (as SES network in Greece) for more definite conclusions.

#### **5. Discussion of LE features**

To use the LE for EQ prediction, one needs to know its lead time, amplitude, frequency characteristic, and expected distribution of sensitive places in the Earth


∆*r, distance between observatory and EQ epicenter (or nearby displacement fault, given in brackets);* ∆*t, lead time of LE appearance before the EQ; A, LE amplitude; f, frequencies at which LE was recorded or the maximum of LE frequency characteristic. Scatter of A/*∆*r ratio shows strong irregularities in spatial decay of LE***.**

#### **Table 2.**

*Parameters of the observed LE.*

surface. This knowledge can be obtained now only empirically. We can extract the necessary properties from the data presented in Section 1.3 supplementing them with other published data. An attempt of such extraction is presented in **Table 2**.

The results depend of the conditions of observation. So, sampling rate of 10 min and compressed time scale in [12] describing two EQs in Taiwan exclude frequency content estimation. Important parameter – lead time ∆t is properly determined only before Loma Prieta EQ when signal-to-noise ratio was large during long time that allowed separate three stages of the precursor appearance. Spatial selectivity complicates the formulation of the LE spatial regularities. Thus, we are in the very beginning of LE phenomenon study and use.

#### **6. Conclusions**

We have calculated induction vectors using data from Japanese observatories for many years preceding the 2011 Tohoku EQ. In 2008–2010 at six observatories, we found anomalous variations of induction vectors, which are regarded as middleterm EQ precursors. Those observatories are located not at the shortest distances from the EQ epicenter, which is in general agreement with the well-known phenomenon of spatial selectivity of EQ precursors. The analysis of horizontal tensors reveals a conductivity anomaly under the central part of the Boso peninsula with a WNW-ESE strike coinciding both with the Sagami trough strike and well conducting 3-km-thick sediment strike. A joint analysis of geoelectric and tectonic data leads to a preliminary conclusion that the Boso conductivity anomaly connects two large-scale conductors: Pacific seawater and a deep magma reservoir beneath a volcanic belt. Similar anomaly was found earlier in Kamchatka [21]. Then, applying original data analysis with the elimination of annual and monthly variations, we separated two-month-long short-term EQ precursor of the Tohoku EQ.

Several cases of lithosphere emission LE before strong EQs were reviewed and analyzed, and preliminary portrait of LE precursor was compiled: LE can appear several times with lead time a month(s), weeks, days, hours, and minutes and can attain amplitude several hundreds of nT which rapidly and not uniformly diminishes with moving away from the source. Typical frequency content/maximum is 0.01–0.5 Hz. As it is widely accepted [5], LE is generated by the process of

**105**

**Author details**

Ukraine

Igor I. Rokityansky\*, Valeriia I. Babak and Artem V. Tereshyn

\*Address all correspondence to: rokityansky@gmail.com

provided the original work is properly cited.

Ukrainian National Academy of Sciences, Subbotin Institute of Geophysics, Kiev,

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

microcracks opening in the course of EQ preparation and should be a rather common phenomenon. It is not quite clear how high-frequency microcrack radiation propagates through many kilometers of the Earth's crust to be recorded at the Earth surface. Seemingly, the radiation finds the optimal pathways leading to sensitive places on the earth surface where signal can be observed. Then, the search of sensi-

1.Network must allow the gradient measurements, so a minimum of three magnetometers must be installed for synchronous records [24].

2.The best but very expensive is the SES monitoring network in Greece. Electrical dipoles can be supplemented or replaced by magnetometers. We recommended for use the practice of sensitive places search and use [11] and the methodology of LE sophisticated analysis developing by Prof. Varotsos'

3.RF approach is a valuable supplement to LE. It has lower temporal resolution but yields additional information on the conductivity variations in the EQ

tive spots opens new channel of information for the Earth interior study. Recommendation on the LE monitoring for the strong EQ prediction

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

team [14, 15].

preparation zone.

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

microcracks opening in the course of EQ preparation and should be a rather common phenomenon. It is not quite clear how high-frequency microcrack radiation propagates through many kilometers of the Earth's crust to be recorded at the Earth surface. Seemingly, the radiation finds the optimal pathways leading to sensitive places on the earth surface where signal can be observed. Then, the search of sensitive spots opens new channel of information for the Earth interior study. Recommendation on the LE monitoring for the strong EQ prediction

1.Network must allow the gradient measurements, so a minimum of three

magnetometers must be installed for synchronous records [24].


### **Author details**

*Seismic Waves - Probing Earth System*

Loma Prieta M7.1 7 36 day,

Taiwan Chi-Chi M7.6 80 (≈5) >32 day,

surface. This knowledge can be obtained now only empirically. We can extract the necessary properties from the data presented in Section 1.3 supplementing them with other published data. An attempt of such extraction is presented in **Table 2**. The results depend of the conditions of observation. So, sampling rate of 10 min and compressed time scale in [12] describing two EQs in Taiwan exclude frequency content estimation. Important parameter – lead time ∆t is properly determined only before Loma Prieta EQ when signal-to-noise ratio was large during long time that allowed separate three stages of the precursor appearance. Spatial selectivity complicates the formulation of the LE spatial regularities. Thus, we are in the very

**Earthquake ∆r, km ∆t, day or hour A, nT f, Hz A/∆r, nT/km** Alaska M9.2 440 (30) 1 h 100 0.28 (3.3)

> 13 day, 3–0 h

10–2 days

Spitak M6.9 130 4 h 0.1 0.1–1 0.001 Racha aftershock M6.2 ≈50 4–1 days, few h ≈1 0.1–1 0.02 Racha aftershock M4 35 Hours 1 0.1–1 0.029

∆*r, distance between observatory and EQ epicenter (or nearby displacement fault, given in brackets);* ∆*t, lead time of LE appearance before the EQ; A, LE amplitude; f, frequencies at which LE was recorded or the maximum of LE* 

Greneva-Kozani M6.6 80 25 days ≈1? ≈0.05?

*frequency characteristic. Scatter of A/*∆*r ratio shows strong irregularities in spatial decay of LE***.**

1.5, 2, 5

0.01–0.5 0.21

200 2.5 (40)

0.29 0.71

We have calculated induction vectors using data from Japanese observatories for many years preceding the 2011 Tohoku EQ. In 2008–2010 at six observatories, we found anomalous variations of induction vectors, which are regarded as middleterm EQ precursors. Those observatories are located not at the shortest distances from the EQ epicenter, which is in general agreement with the well-known phenomenon of spatial selectivity of EQ precursors. The analysis of horizontal tensors reveals a conductivity anomaly under the central part of the Boso peninsula with a WNW-ESE strike coinciding both with the Sagami trough strike and well conducting 3-km-thick sediment strike. A joint analysis of geoelectric and tectonic data leads to a preliminary conclusion that the Boso conductivity anomaly connects two large-scale conductors: Pacific seawater and a deep magma reservoir beneath a volcanic belt. Similar anomaly was found earlier in Kamchatka [21]. Then, applying original data analysis with the elimination of annual and monthly variations, we

separated two-month-long short-term EQ precursor of the Tohoku EQ.

Several cases of lithosphere emission LE before strong EQs were reviewed and analyzed, and preliminary portrait of LE precursor was compiled: LE can appear several times with lead time a month(s), weeks, days, hours, and minutes and can attain amplitude several hundreds of nT which rapidly and not uniformly diminishes with moving away from the source. Typical frequency content/maximum is 0.01–0.5 Hz. As it is widely accepted [5], LE is generated by the process of

beginning of LE phenomenon study and use.

**6. Conclusions**

**Table 2.**

*Parameters of the observed LE.*

**104**

Igor I. Rokityansky\*, Valeriia I. Babak and Artem V. Tereshyn Ukrainian National Academy of Sciences, Subbotin Institute of Geophysics, Kiev, Ukraine

\*Address all correspondence to: rokityansky@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Wang K, Chen Q-F, Sun S, Wang A. Predicting the 1975 Haicheng earthquake. Bulletin of the Seismological Society of America. June 2006;**96**(3): 757-795. DOI: 10.1785/0120050191

[2] Rokityansky II. Geoelectromagnetic Investigation of the Earth's Crust and Mantle. Berlin Heidelberg New York: Springer-Verlag; 1982. 381 p

[3] Berdichevsky MN, Dmitriev VI. Models and Methods of Magnetotellurics. Berlin Heidelberg: Springer-Verlag; 2008. 564 p. DOI: 10.1007/978-3-540-77814-1

[4] Chave AD, Jones AG, editors. The Magnetotelluric Method. Cambridge: Cambridge University Press; 2012. 584 p. DOI: 10.1017/CBO9781139020138.002

[5] Surkov V, Hayakawa M. Ultra and Extremely Low Frequency Electromagnetic Fields. London: Springer Geophysics; 2014. 486 p. DOI: 10.1007/978-4-431-54367-1

[6] Moore GW. Magnetic disturbances preceding the 1964 Alaska earthquake. Nature. 1964;**203**:508-509. DOI: 10.1038/203508b0

[7] Frather-Smith AC, Bernardi A, McGill PR, Ladd ME, Helliwell RA, Villard OG Jr. Low-frequency magnetic field measurements near the epicenter of the Ms 7.1 Loma Prieta earthquake. Geophysical Research Letters. 1990;**17**(9):1465-1468. DOI: 10.1029/ GL017i009p01465

[8] Kopytenko YA, Matiashvili TG, Voronov PM, Kopytenko EA, Molchanov OA. Detection of ultralow-frequency emissions connected with Spitak earthquake and its aftershock activity, based on geomagnetic pulsations data at Dusheti and Vardzia observatories. Physics of the Earth and Planetary Interiors. 1993;**77**:85-95

[9] Kopytenko YA, Matiashvili TG, Voronov PM, Kopytenko EA. Observation of electromagnetic ultralow-frequency lithospheric emission in the Caucasian seismically active zone and their connection with earthquakes. In: Hayakawa b M, Fujinawa Y, editors. Electromagnetic Phenomena Related to Earthquake Prediction. Tokyo: Terra Scientific Publishing Company (TERRAPUB); 1994. pp. 175-180

[10] Rokityansky II. Spatial selectivity of earthquake's precursors. Physics and Chemistry of the Earth. 2006;**31**: 204-209. DOI: doi.org/10.1016/j. pce.2006.02.028

[11] Varotsos AP. The Physics of Seismic Electric Signals. Tokyo, Japan: TERRAPUB; 2005. 338 p

[12] Tsai YB, Liu JY, Ma KF, Yen HY, Chen KS, Chen YI, et al. Precursory phenomena associated with the 1999 chi-chi earthquake in Taiwan as identified under the ISTEP program. Physics and Chemistry of the Earth. 2006;**31**:365-377

[13] Varotsos P, Alexopoulos K, Lazaridou M. Latest aspects of earthquake prediction in Greece based on seismic electric signals, II. Tectonophysics. 1993;**224**:1-37. DOI: 10.1016/0040-1951(93)90055-O

[14] Varotsos PA, Sarlis NV, Skordas ES, Lazaridou MS. Seismic electric signals: An additional fact showing their physical interconnection with seismicity. Tectonophysics. 2013;**589**:116-125. DOI: 10.1016/j. tecto.2012.12.020

[15] Sarlis NV, Skordas ES, Varotsos PA, Nagao T, Kamogawa M, Tanaka H, et al. Minimum of the order parameter fluctuations of seismicity before major earthquakes in Japan. Proceedings of the National Academy of Sciences of the United States of America.

**107**

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes*

2007. pp. 259-275. DOI: 10.1016/ S0076-6895(06)40010-X

[23] Klymkovych TA. Peculiarities of temporal variations of anomalous magnetic field and induction vectors in the Transcarpathian seismic-active trough [PhD thesis] Kiev: Institute of Geophysics; 2009 (in Ukrainian)

[24] Kopytenko YA, Ismaguilov VS, Hattori K, Hayakawa M. Anomaly disturbances of the magnetic fields before the strong earthquake in Japan on march 11, 2011. Annals of Geophysics (Italy). 2012;**55**(1):101-107. DOI:

[25] Suzuki H. Underground geological structure beneath the Kanto plain, Japan. National Research Institute for Earth Science and Disaster Prevention,

[26] Takahashi M, Yanagisawa Y, Hayashi H, Kasahara K, Ikawa T, Kawanaka T, et al. Miocene subsurface half-grabens in the Kanto plain, Central Japan. Proceeding of International Workshop on Strong Ground Motion Prediction and Earthquake Tectonics in

[27] Tregubenko VI. Seismoprognostic researches. In: Goshovsky SV, editor. 50 Years of Ukrainian State Geological Institute (1957-2007). Anniversary Directory. Kyiv: Ukr SGPI; 2007.

10.4401/ag-5260

Japan. 2002;**63**:1-19

Urban Areas. 2005:65-74

pp. 52-56 (in Ukrainian)

*DOI: http://dx.doi.org/10.5772/intechopen.88522*

2013;**110**:13734-13738. DOI: 10.1073/

[16] Yanagihara K, Nagano T. Time changes of transfer function in the Central Japan anomaly of conductivity with special reference to earthquake occurrences. Journal of Geomagnetism and Geoelectricity. 1976;**28**(2):157-163

[17] Fujita S. Monitoring of time changes of conductivity anomaly transfer functions at Japanese magnetic observatory network. Memoirs of the Kakioka Magnetic Observatory.

[18] Fujiwara S. Temporal changes of geomagnetic transfer functions using data obtained mainly by the geographical survey institute. Bull Bulletin of the Geographical Survey

[19] Rokityansky II, Tregubenko VI, Babak VI, Tereshyn AV. Induction vector and horizontal tensor components variations before the Tohoku earthquake on the 11th march 2011 according to the data of Japanese geomagnetic observatories. Geophysical Journal. 2013;**35**(3):115-130. (in Russian)

[20] Rokityansky II, Babak VI, Tereshyn AV. Geomagnetic activity impacts on the results of the induction vector calculations. Geophysical Journal.

2015;**37**(6):86-98. (in Russian)

[21] Rokityansky II, Babak VI,

response functions prior to the Tohoku, Japan earthquake. Journal of Volcanology and Seismology.

[22] Varentsov IM. Arrays of

simultaneous EM soundings: Design, data processing and analysis. In: Spichak V, editor. EM Sounding of the Earth's Interior. Methods in Geochemistry and Geophysics. Vol. 40. Heidelberg, London: Elsevier;

2016;**10**(6):78-91

Tereshyn AV. An analysis of geomagnetic

pnas.1312740110

1990;**23**:53-87

Institute. 1996;**41**:1-25

*Low-Frequency Electromagnetic Signals Observed before Strong Earthquakes DOI: http://dx.doi.org/10.5772/intechopen.88522*

2013;**110**:13734-13738. DOI: 10.1073/ pnas.1312740110

[16] Yanagihara K, Nagano T. Time changes of transfer function in the Central Japan anomaly of conductivity with special reference to earthquake occurrences. Journal of Geomagnetism and Geoelectricity. 1976;**28**(2):157-163

[17] Fujita S. Monitoring of time changes of conductivity anomaly transfer functions at Japanese magnetic observatory network. Memoirs of the Kakioka Magnetic Observatory. 1990;**23**:53-87

[18] Fujiwara S. Temporal changes of geomagnetic transfer functions using data obtained mainly by the geographical survey institute. Bull Bulletin of the Geographical Survey Institute. 1996;**41**:1-25

[19] Rokityansky II, Tregubenko VI, Babak VI, Tereshyn AV. Induction vector and horizontal tensor components variations before the Tohoku earthquake on the 11th march 2011 according to the data of Japanese geomagnetic observatories. Geophysical Journal. 2013;**35**(3):115-130. (in Russian)

[20] Rokityansky II, Babak VI, Tereshyn AV. Geomagnetic activity impacts on the results of the induction vector calculations. Geophysical Journal. 2015;**37**(6):86-98. (in Russian)

[21] Rokityansky II, Babak VI, Tereshyn AV. An analysis of geomagnetic response functions prior to the Tohoku, Japan earthquake. Journal of Volcanology and Seismology. 2016;**10**(6):78-91

[22] Varentsov IM. Arrays of simultaneous EM soundings: Design, data processing and analysis. In: Spichak V, editor. EM Sounding of the Earth's Interior. Methods in Geochemistry and Geophysics. Vol. 40. Heidelberg, London: Elsevier;

2007. pp. 259-275. DOI: 10.1016/ S0076-6895(06)40010-X

[23] Klymkovych TA. Peculiarities of temporal variations of anomalous magnetic field and induction vectors in the Transcarpathian seismic-active trough [PhD thesis] Kiev: Institute of Geophysics; 2009 (in Ukrainian)

[24] Kopytenko YA, Ismaguilov VS, Hattori K, Hayakawa M. Anomaly disturbances of the magnetic fields before the strong earthquake in Japan on march 11, 2011. Annals of Geophysics (Italy). 2012;**55**(1):101-107. DOI: 10.4401/ag-5260

[25] Suzuki H. Underground geological structure beneath the Kanto plain, Japan. National Research Institute for Earth Science and Disaster Prevention, Japan. 2002;**63**:1-19

[26] Takahashi M, Yanagisawa Y, Hayashi H, Kasahara K, Ikawa T, Kawanaka T, et al. Miocene subsurface half-grabens in the Kanto plain, Central Japan. Proceeding of International Workshop on Strong Ground Motion Prediction and Earthquake Tectonics in Urban Areas. 2005:65-74

[27] Tregubenko VI. Seismoprognostic researches. In: Goshovsky SV, editor. 50 Years of Ukrainian State Geological Institute (1957-2007). Anniversary Directory. Kyiv: Ukr SGPI; 2007. pp. 52-56 (in Ukrainian)

**106**

1993;**77**:85-95

*Seismic Waves - Probing Earth System*

[1] Wang K, Chen Q-F, Sun S,

**References**

Springer-Verlag; 1982. 381 p

Models and Methods of

10.1007/978-3-540-77814-1

Wang A. Predicting the 1975 Haicheng earthquake. Bulletin of the Seismological Society of America. June 2006;**96**(3): 757-795. DOI: 10.1785/0120050191

[9] Kopytenko YA, Matiashvili TG, Voronov PM, Kopytenko EA. Observation of electromagnetic ultralow-frequency lithospheric emission in the Caucasian seismically active zone and their connection with earthquakes. In: Hayakawa b M, Fujinawa Y, editors. Electromagnetic Phenomena Related to Earthquake Prediction. Tokyo: Terra Scientific Publishing Company (TERRAPUB); 1994. pp. 175-180

[10] Rokityansky II. Spatial selectivity of earthquake's precursors. Physics and Chemistry of the Earth. 2006;**31**: 204-209. DOI: doi.org/10.1016/j.

[11] Varotsos AP. The Physics of Seismic Electric Signals. Tokyo, Japan:

[12] Tsai YB, Liu JY, Ma KF, Yen HY, Chen KS, Chen YI, et al. Precursory phenomena associated with the 1999 chi-chi earthquake in Taiwan as identified under the ISTEP program. Physics and Chemistry of the Earth.

[13] Varotsos P, Alexopoulos K, Lazaridou M. Latest aspects of earthquake prediction in Greece based on seismic electric signals, II. Tectonophysics. 1993;**224**:1-37. DOI: 10.1016/0040-1951(93)90055-O

[14] Varotsos PA, Sarlis NV,

tecto.2012.12.020

Skordas ES, Lazaridou MS. Seismic electric signals: An additional fact showing their physical interconnection with seismicity. Tectonophysics. 2013;**589**:116-125. DOI: 10.1016/j.

[15] Sarlis NV, Skordas ES, Varotsos PA, Nagao T, Kamogawa M, Tanaka H, et al. Minimum of the order parameter fluctuations of seismicity before major earthquakes in Japan. Proceedings of the National Academy of Sciences of the United States of America.

TERRAPUB; 2005. 338 p

pce.2006.02.028

2006;**31**:365-377

[2] Rokityansky II. Geoelectromagnetic Investigation of the Earth's Crust and Mantle. Berlin Heidelberg New York:

[3] Berdichevsky MN, Dmitriev VI.

Magnetotellurics. Berlin Heidelberg: Springer-Verlag; 2008. 564 p. DOI:

[4] Chave AD, Jones AG, editors. The Magnetotelluric Method. Cambridge: Cambridge University Press; 2012. 584 p. DOI: 10.1017/CBO9781139020138.002

[5] Surkov V, Hayakawa M. Ultra and Extremely Low Frequency Electromagnetic Fields. London: Springer Geophysics; 2014. 486 p. DOI:

[6] Moore GW. Magnetic disturbances preceding the 1964 Alaska earthquake. Nature. 1964;**203**:508-509. DOI:

[7] Frather-Smith AC, Bernardi A, McGill PR, Ladd ME, Helliwell RA, Villard OG Jr. Low-frequency magnetic field measurements near the epicenter of the Ms 7.1 Loma Prieta earthquake.

Geophysical Research Letters. 1990;**17**(9):1465-1468. DOI: 10.1029/

[8] Kopytenko YA, Matiashvili TG, Voronov PM, Kopytenko EA, Molchanov OA. Detection of ultralow-frequency emissions connected with Spitak earthquake and its aftershock activity, based on

geomagnetic pulsations data at Dusheti and Vardzia observatories. Physics of the Earth and Planetary Interiors.

10.1007/978-4-431-54367-1

10.1038/203508b0

GL017i009p01465

## *Edited by Masaki Kanao and Genti Toyokuni*

The importance of seismic wave research lies not only in our ability to understand and predict earthquakes and tsunamis, but it also reveals information on the Earth's composition and features in much the same way as it led to the discovery of Mohorovicic's discontinuity. As our theoretical understanding of the physics behind seismic waves has grown, physical and numerical modeling have greatly advanced and now augment applied seismology for better prediction and engineering practices. This book demonstrates the latest techniques and advances in seismic wave analysis from a theoretical approach, data acquisition and interpretation, to analyses and numerical simulations, as well as research applications. The major topics in this book cover aspects on seismic wave propagation, characteristics of their velocities and attenuation, deformation process of the Earth's medium, seismic source process and tectonic dynamics with relating observations, as well as propagation modeling of seismic waves.

Published in London, UK © 2019 IntechOpen © Andrey\_A / iStock

Seismic Waves - Probing Earth System

Seismic Waves

Probing Earth System

*Edited by Masaki Kanao and Genti Toyokuni*