Electrical Conductors Beneath Mt. Erciyes Imaged by Three-dimensional Modeling of Magnetotellurics Data

Earlier studies propose that the volcanic activity embodying the polygenetic Mt. Erciyes in the Cappadocian Volcanic Province (CVP), Central Anatolia, Türkiye, transpired as an inevitable product of the post-collisional extension experienced along two entities, the Anatolide-Tauride Carbonate Block, and the Central Anatolian Crystalline Complex (CACC). With its sixty-four monogenetic vents, Mt. Erciyes is the highest and most voluminous (3300 km²) stratovolcano in Central Anatolia with its summit reaching as high as 3917m. Strain-partitioning played a key role in the formation of the fault systems and the Erciyes basin that favored the evolution of the volcano. During three survey campaigns conducted in 2013, 2014, and 2018, a total of thirty-eight wide-band magnetotellurics (MT) observations were systematically made unravel the electrical structure beneath the Erciyes stratovolcano complex and the adjacent Erciyes basin, as part of a research initiative funded by the NSF under the title Continental Dynamics / Central Anatolian Tectonics (CD/CAT). Defining the boundaries of the Erciyes volcanic complex, the basin exhibits prominent substantial, particularly three major faults, the Yeşilhisar, Develi and Gesi Faults, with the two of them framing the western and eastern edge and the last delineating runs in the middle of the basin. The Gesi Fault crosses from the central part of the basin and acts as the main branch of the wider Central Anatolian Fault (CAF) Zone. Based on geological evidence, the volcano developed in the Pliocene and Quaternary in two stages. These are the (i) Koç Dağ (>2.8 Ma) and the (ii) New Erciyes (<2.8 Ma) stages with various magmatism types, respectively. In this study, phase tensor analyzes were performed on the electrical conductivity structure beneath Mount Erciyes, the summit region and surrounding data collected from thirty-eight observation points, leading to the development of three-dimensional models using the ModeM inversion algorithm in two different ways, with and without topography information.