6-1. Heat Flow
Compared with the previous study by Tanaka (2004), the spatial distribution of crustal heat flow characteristics shows almost the same trend. By interpolating the forearc side, where the amount of data was previously small, it can be said that the entire Tohoku region can now be covered, although the amount of data for the plains in the northern region is relatively small. In the Ou Mountains, where the present volcanic front is located, the heat flux is high, but on the fore-arc side, the heat flux is slightly higher than VF, about 100 mW/m2 in some areas.
The position of the VF in the Tohoku region was about 30-40 km east of its present position at 16 Ma, but it has moved from about 10 km west to east at 10 Ma (Yoshida et al., 2013). It is conceivable that these past VF movements may still have left an impact on the thermal structure of the crust. Since 8 Ma, many large calderas have formed along the central axis of the Ou spine (Yoshida et al., 2013), but only one caldera has been identified on the forearc side of the present VF.
The time required to cool a magma reservoir with a diameter of 10 km is said to be about 1 Ma (Tomiya, 2000), so the time scales may not match. On the other hand, there are cases where calderas are assumed to have been active for more than 600,000 years after their formation (Takehara et al., 2017), and hydrothermal reservoirs and low-velocity bodies have been observed beneath calderas formed in the Late Miocene (Sato et al., 2002). It has also been pointed out that magma reservoirs with lifetimes longer than several million years may exist if conditions like continuous fluid supply from deep underground are met (Yoshida et al. 2020). Therefore, it becomes important to compare the subsurface and temperature structures in high heat flow regions.
Temperature gradients associated with rising hydrothermal fluids can significantly impact regions around volcanoes.
Sakagawa et al. (2006) analyzed the crustal heat flux due to heat conduction and the heat flux due to fluid involvement in many borehole wells and estimated that as much heat as the heat conduction flux is transported to the surface by fluids.
Furthermore, Tamanyu (2008) proposed a model of hydrothermal convection related to the thickness of the sedimentary layers in each region and found that hydrothermal convection is dominant down to the depth of the Proterozoic basement rocks, from 1 to 3 km in plains and basins, and up to 1 km in volcanic regions. In such geothermal regions, hydrothermal convection systems are dominant. Therefore, in geothermal regions such as volcanic areas, the crustal heat flow rate may be overestimated when estimating the temperature structure at depths deeper than a few kilometers.
On the other hand, it has been pointed out that groundwater flow systems are widespread in the plains (Miyakoshi et al., 2001). In these areas, subsurface temperature gradients are complex, with large temperature gradients in the ascending groundwater basins and small temperature gradients in the descending basins (Uchida et al., 2014). For example, Kaneko et al. (2020) modeled the groundwater flow in the Sendai Plain; the Hi-net Sendai station is located in an area where the subsurface temperature is relatively high, and the temperature profile shows an upward flow type in the shallow part, which is consistent with this groundwater flow model.
On the other hand, most of the D-class wells, which were judged to have powerful groundwater influence, are located in the plains with thick sedimentary layers, and their temperature profiles show downward flow type. The temperature profiles of the Hi-net borings showed the influence of surface groundwater in about 10% of the stations, including the C-class wells that were judged to be partially affected.
Based on these results, more careful analysis considering the influence of groundwater may be necessary for borehole wells located in geological conditions where sedimentary layers are thick, and water can easily penetrate, especially in basins and plains.
6-2 Thermal Structure
In order to examine the validity of the calculated temperature structure, we first compare it with the D90 distribution of Omuralieva et al. (2012), which is an indicator of the lower limit of the seismogenic layer of the crust. There seems to be a good correlation between the temperature structure and the spatial distribution of D90, and the isotherm at a depth of 400°C is more correlated than the isotherm at 300°C. The effect of introducing detailed crustal structure can be seen from the good correlation in the plains of the southern part of the Japan Sea, the epicenter of the 2004 Niigata-Chuetsu earthquake. However, compared to D90, the estimated temperature structure tends to be slightly higher, especially along the Ou Spine Mountains. On the other hand, there are also some areas where the temperature is estimated to be lower, mainly in the plains.
For a more accurate estimation, it may be useful to use an approach proposed by Sakagawa et al. (2004) to elaborately model the heat flux, which is the sum of heat conduction in the rock mass and heat transport by the fluid, as observed heat flow at the surface. In the future, it will be necessary to collaborate with groundwater models, for example, to separate the heat flux from the surface to 1 to 2 km, where the influence of fluid is significant, from the heat conduction below the base rock conduction is dominant.
Next, we compare it with the Curie point temperature distribution by Ohkubo et al. (1989). This distribution, interpreted by Nishida and Hashimoto (2007) as corresponding to 400-450°C, seems to have an excellent spatial correlation. Although both have resolution limitations, there seems to be a good correlation.
One way to verify the results of temperature calculations in deeper regions is to compare them with simulations of the temperature structure associated with plate subduction. Typically, it would be desirable to compare the estimated temperatures near the upper surface of the plate, but since the boundary of the subducted Pacific plate is deeper than 40 km in the Tohoku region, a simple comparison is difficult. On the other hand, when the temperature structure is compared with the hot finger model (Tamura et al., 2002), in which particularly hot areas of the mantle wedge are distributed at regular intervals, the spatial distribution of regions that are hotter than their surroundings appears to be in good agreement. Again, however, a quantitative comparison may be difficult in this study because the calculations are based on a simplified model above the Solidus temperature.
In this study, the crustal structure is assumed to be a simple horizontal layered structure with an upper crustal thickness of 18 km and a lower crustal thickness of 12 km. In many models, the Moho surface is estimated to be deeper just below the Ou Mountains and slightly shallower on the frontal and back-arc sides (e.g., Nishimoto et al., 2005, Muto and Ohzono, 2012, Matsubara et al., 2017A), significantly since the thickness of the upper crust determines the total amount of crustal heat generation, and thus has a significant impact on the estimation of the temperature structure of the lower crust. Further discussion based on detailed structural models is needed; since the 3D seismic velocity structure shows a heterogeneous structure (e.g., Matsubara et al., 2017B), it is likely that the crustal constituents are not simply horizontally layered (e.g., Ishikawa et al., 2017). Since the thermal conductivity and the amount of radiative heat generation vary depending on the type of rock, it will be necessary to construct a 3-D structure that takes these characteristics into account.
Nakajima and Hasegawa (2003) proposed a model in which an S-wave reflection surface exists on the east side of the volcanic front and water is supplied from the lower crust. It will be necessary to study the effect of such fluid moving from the lower crust to the upper crust on the thermal structure.
In addition, the Tohoku region is an area where tectonic inversion is in progress (Sato 1994), and as Fukahata (2000) points out, the influence of the crust needs to be taken into account. If these issues can be overcome, it may be possible to improve the accuracy required for comparison with D90 and improve the accuracy of temperature estimation to the Moho surface.