Advancing Permafrost Monitoring With Autonomous Electrical Resistivity Tomography (A‐ERT): Low‐Cost Instrumentation and Open‐Source Data Processing Tool

Abstract

Abstract Permafrost is a widespread phenomenon in the cold regions of the globe and is under-represented in global monitoring networks. This study presents a novel low-cost, low-power, and robust Autonomous Electrical Resistivity Tomography (A-ERT) monitoring system and open-source processing tools for permafrost monitoring. The processing workflow incorporates diagnostic and filtering tools and utilizes open-source software, ResIPy, for data inversion. The workflow facilitates quick and efficient extraction of key information from large data sets. Field experiments conducted in Antarctica demonstrated the system's capability to operate in harsh and remote environments and provided high-temporal-resolution imaging of ground freezing and thawing dynamics. This data set and processing workflow allow for a detailed investigation of how meteorological conditions impact subsurface processes. The A-ERT setup can complement existing monitoring networks on permafrost and is suitable for continuous monitoring in polar and mountainous regions, contributing to cryosphere research and gaining deeper insights into permafrost and active layer dynamics. Plain Language Summary Permafrost, frozen ground in cold regions, has significant impacts on the global environment. Monitoring of permafrost is crucial because it influences the global carbon cycle, hydrology, contaminant movement, and ecosystem stability. However, current monitoring systems have limitations, particularly in remote regions like Antarctica. To tackle this challenge, a new monitoring system, Autonomous Electrical Resistivity Tomography (A-ERT), was introduced. A-ERT is a geophysical technique that employs electrical signals to study ground freezes and thaws with high precision over time. Alongside this, open-source processing tools were developed to process obtained A-ERT data and efficiently extract essential information from large data sets. The developed A-ERT system is robust, low-cost, low-power, and designed to operate in harsh conditions. Tested in Antarctica, our findings show that A-ERT data combined with processing pipelines offers a valuable tool for examining freezing and thawing processes in extreme environments. The proposed setup can contribute to a network of autonomous permafrost monitoring systems, important for cryosphere research and advancing our understanding of climate change's impact on permafrost dynamics.