Vapor Layer Fluctuations Estimated by Continuous EM-ACROSS Method Observations at Inferno Crater Lake

<p>Phreatic eruptions are primarily driven by vapor layers, making the detection of changes in these layers essential for volcanic disaster prevention. Inferno Crater Lake in New Zealand, characterized by its periodic 38-day fluctuations in water level and temperature, is hypothesized to experience vapor layer variations that contribute to these phenomena. To investigate this, a six-month observation campaign was conducted in 2023 using the EM ACROSS method, a geophysical technique sensitive to high-resistivity layers. This method involved continuous transmission of artificial electromagnetic signals, allowing precise monitoring of subsurface resistivity structures. By focusing on frequencies near the transmission frequency, errors in electric field and current measurements were evaluated, enabling observations with a time resolution of one hour. Variations in the amplitude and phase of the apparent resistivity tensor were found to correlate strongly with fluctuations in the lake's water level. However, significant phase variations were not observed below 46.95 Hz, and the phase tensor was undetectable in this frequency range. Resistivity fluctuations at these lower frequencies were attributed to changes at depths of approximately 300 m, suggesting that the sensitivity of the method decreases with depth. To further interpret the observed resistivity changes, a 3-D finite element method was employed to model the subsurface resistivity structure. The results indicate that a vapor layer expanding to a thickness of 180–240 m and rising to 60 m below the surface during high water levels provided the best explanation for the observed phase tensor variations. This finding aligns with previous resistivity surveys that identified a resistivity-altered zone near the lake, although the EM-ACROSS method demonstrated greater sensitivity to deeper regions. These results highlight the potential of the EM-ACROSS method as a highly sensitive tool for monitoring vapor layer dynamics, which are critical to understanding and forecasting phreatic eruption processes. The method’s ability i to provide high-resolution temporal and spatial data makes it particularly valuable for observing phreatomagmatic systems, offering new insights into subsurface resistivity changes and their relationship with surface-level phenomena. Future applications of this method could significantly enhance volcanic monitoring efforts and improve predictive capabilities for eruption-related hazards.</p>