Landslides are a major hazard in mountainous regions of the Ecuadorian Andes. This study examines the upper and accessible sector of the complex San José de Aloburo landslide, Imbabura Province, by integrating electrical resistivity tomography (ERT) with surface geological observations, three stratigraphic columns, and local grain-size information. Four Wenner-array ERT profiles were acquired with a low-cost, non-commercial system and imaged to approximately 35–40 m depth. The inverted sections contain broad low-resistivity domains (approximately 4–45 Ω m) and higher-resistivity domains reaching approximately 297 Ω m. Because electrical resistivity is non-unique with respect to lithology, moisture, porosity, weathering, and pore-fluid properties, these domains are interpreted jointly with the geological observations rather than as direct indicators of saturation, cohesion, or a mechanically verified slip surface. Geoelectrical boundaries in Profiles 1, 2, and 4 are spatially consistent with potential instability-related boundaries in the upper landslide sector, but this interpretation remains indirect and lacks borehole or geotechnical confirmation at depth. The stratigraphic columns document alternating ash and pumice/lapilli units, whereas the quantitative sieve analysis available for sample ANG-TOP-B-01 provides only local sedimentological support and is not extrapolated to the entire landslide. The integrated dataset demonstrates the value of combining ERT and field geology in a volcaniclastic Andean setting while also defining the limitations imposed by survey coverage, inversion non-uniqueness, seasonal hydrological variability, and incomplete archival documentation of the custom instrumentation.
There are numerous subglacial lakes in Antarctica, typically covered by thick ice sheets. Qilin Subglacial Lake is one of the largest subglacial lakes in Antarctica, lying beneath approximately 3600 m of ice. The exploration of this unique environment is of considerable scientific importance. RECoverable Autonomous Sonde (RECAS) has been proposed for exploring Qilin Subglacial Lake. However, drilling into the lakes with such probe may be impeded by volcanic ash or small rock clasts within the ice sheet. In addition, RECAS is incapable of withstanding the extreme hydrostatic pressure existing in the Qilin Subglacial Lake. To address these challenges, the thermal head of RECAS was redesigned and fabricated. Compared with the original RECAS thermal head, the updated thermal head has extra water circulation unit. Laboratory test validated that the redesigned RECAS thermal head can operate at water pressures of up to 40 MPa. Moreover, its rate of penetration (ROP) improved by 22 % in clean ice, by 41 % in dust-laden ice, and by 253 % in ice with debris-rich ice. The updated RECAS thermal head is expected to be utilized to drill Qilin Subglacial Lake in the coming Antarctic work season.
Ultra–low-noise inertial sensors are a cornerstone of modern geoscientific instrumentation, enabling high-resolution observations across seismology, geodesy, gravimetry, and vibration isolation. Achieving and reliably predicting their performance requires a rigorous treatment of physical causality, noise propagation, and uncertainty, particularly in force-feedback architectures operating near fundamental limits. In this study, we introduce a causal and uncertainty-aware digital-twin framework for the design and metrological assessment of ultra–low-noise geoscientific inertial sensors. The proposed framework integrates mechanical dynamics, force-feedback control, transduction, and digital acquisition within a physically realisable model that explicitly enforces causality and stability constraints. Starting from a minimal equation-of-motion description, the digital twin is formulated in the frequency domain to construct causal transfer functions and a comprehensive noise-budget model. The framework enables the systematic separation of fundamental thermal noise limits from implementation-dependent noise sources, including readout, actuation, and digital acquisition effects. We introduce quantitative performance metrics based on self-noise spectra, dominant noise regimes, crossover frequencies, and near-plateau bandwidths, allowing complex spectral behaviour to be condensed into actionable design indicators. Parameter uncertainties are propagated through the digital twin to provide uncertainty-aware performance estimates and robustness diagnostics. Through a series of illustrative analyses, we demonstrate how the proposed digital twin supports informed design trade-offs, identifies performance bottlenecks, and prevents non-physical or overly optimistic sensitivity estimates arising from non-causal modelling assumptions. While focused on inertial sensors, the methodology is general and transferable to other classes of geoscientific instruments. The framework provides a transparent and extensible foundation for next-generation sensor design, virtual experimentation, and metrologically consistent performance prediction.
Forests provide crucial ecosystem services, but are vulnerable to climate-related physical and biological stresses, such as droughts, pests and pathogens. The rapid climate change currently observed increases the pressure on forest ecosystems, with already drastic consequences, e.g., widespread tree mortality across Central Europe. However, we fall short of understanding underlying process dynamics and their impacts on the Earth system. To better understand and predict forest ecosystem dynamics and the associated energy, carbon and water fluxes, detailed knowledge of ecosystem structure, processes and functioning under constantly varying conditions and across different spatial and temporal scales is needed. The ECOSENSE project brings together engineers, environmental and data scientists to establish novel environmental monitoring approaches and to capture distributed forest carbon and water flux dynamics in space and time with a wide range of established measurement technologies and newly developed sensors. Here, we describe the required infrastructure – called ECOSENSE forest – with regard to physical structures, power supply, communication network and data management, that supports such novel environmental sensor networks. We established a comprehensive monitoring system in this ECOSENSE forest, spanning from below-ground to above-canopy with three large scaffold towers in different plots. More than 670 commercial and 430 self-built sensors monitor over 90 distinct parameters, fluxes, or processes generating upwards of 4500 time series that capture soil, tree and atmosphere processes with high spatial and temporal resolution. In particular, our design objective is to provide a stable, flexible and secure forest research infrastructure with power, communication and data management using low-cost and commercially available components that meet the needs of various research disciplines. Our considerations and experiences provide impulses and practical solutions for establishing robust, distributed field research infrastructures and thus increase data continuity and resilience to disruptions at remote locations. The ECOSENSE forest may thus serve as a blueprint for future projects with similar goals and challenges.
The Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission investigates the coupling between the solar wind and Earth's magnetosphere using five identical spinning spacecraft. Each spacecraft rotates at a predefined rate to stabilize it and carries a suite of instruments, including a fluxgate magnetometer (FGM) that measures the three-dimensional magnetic field. Since 24 May 2024, the FGM on board THEMIS E has no longer recorded the magnetic field component along the spin axis, while the two components approximately within the spin plane remain fully available. We present a method to reconstruct the missing magnetic field component using data from these two remaining components together with the spacecraft spin, yielding full three-component magnetic field vectors at spin period cadence and with an effective bandwidth of 1/60 Hz. The approach was validated using original THEMIS E data from 2017 to 2020, when all three sensor components were available. We further estimated the reconstruction noise floor, indicating that the method is unlikely to be limited by sensor noise. These results demonstrate that on a spinning spacecraft, two components whose sensor axes lie close to, but not exactly in, the spin plane are sufficient to reconstruct three-dimensional magnetic field vectors, allowing continued magnetospheric observations despite the loss of one sensor component.
