Groundwater outflows and fault density spatial relation in the Baikal rift system (Russia)

Abstract

For the Baikal rift system (BRS) territory (Russian Federation) and the Barguzin-Baunt depression branch zone, active faults density is compared with the thermal and cold spring’s quantity and temperature to identify the geospatial statistical relationship of those parameters with a view to quantify the main factors connected with base principles study of modern hydrothermal formation. Statistical calculations show that the hot and cold spring’s number per unit area increases within the active faults number. It is established that an area with active faults density higher, than the mean value, is characterized by the maximum number of thermal springs. Correlation analysis showed that the number of modern mineral water springs per unit area and their temperature depend on the earth’s crust fragmentation degree: zones of reduced density are characterized by rare but hotter thermal springs, and zones of increased density are characterized by numerous and colder thermal vents, which probably connects with water dilution by underground cold waters in a more fractured geological environment.

Influence of crustal fracturing on the thermal springs and earthquake swarms distribution in the north-east part of the Baikal rift system (Russia)

“…There is a direct linear correlation with the correlation coefficient r=0.79 between the values of the heat flux and the probable strength of the earthquake (Pinneker et al 1984). Also, previously, we established an inverse correlation dependence of the hydrothermal water temperature and the density of faults (Novopashina and Kuz'mina 2018). Accordingly, in general, the thermal springs associated with the same density range as the swarms of earthquakes are hotter than the hydrotherms of the more fractured medium.…”

Geofluids as a possible unconventional tool for seismic hazard assessment

“…In particular, we considered the following datasets: i) carbon dioxide emissions (Irwin and Barnes, 1980;Tamburello et al, 2018); ii) heat flow (Lucazeau, 2019); iii) S-wave dispersion (Debayle et al, 2016;Hasterok et al, 2022) and we updated datasets of thermal springs (Waring, 1965;Tamburello et al, 2022) and isotope composition of helium (Abedini et al, 2006). By taking advantage of recently computerized catalogs of seismicity (Storchak et al, 2013), we followed the same approach already utilized in the literature about the investigation of the spatial relationships between the distribution of earthquakes (Figure 1), and the location of anomalous fluid emissions (e.g., Kuz'mina and Novopashina, 2018;Tamburello et at., 2018), to identify areas potentially capable of hosting future strong earthquakes (M>6). A specific advancement of this work was the critical re-evaluation of the helium database by Abedini et al (2006), and its extension via the addition of present-day geofluids data published until 2022.…”

The December 9, 2020, Mw 5.5 Kudara earthquake (Middle Baikal, Russia): internet questionnaire hard test and macroseismic data analysis

“…The depth of the Moho boundary within the Middle Baikal is estimated to be approximately 40 km (Ten Brink and Taylor 2002;Mordvinova et al 2016). The area is distinguished by a rather dense active faults pattern (Levi et al 1997;Lunina 2016;Kuz'mina and Novopashina 2018) with a maximum seismic potential of up to M 7.5 (Ulomov 2014).…”