Open-source Telemetry Instrumentation for Networked and Real-time Glacier Monitoring

In-situ glacier monitoring efforts typically involve periodic acquisitions of data, at time intervals limited to when field sites can be accessed to retrieve and collect data. Although commercial satellite communication technologies can be implemented to transmit data back at periodic intervals, the increased cost of instrumentation and subscription services places such technology out of reach in many applications. The development of Internet of Things (IoT) technology is enabling a new era of networked instruments for monitoring activities. Low-cost and low-power telemetry chips can be readily integrated with existing instrumentation for monitoring diverse glacier processes. Here, we illustrate a recent deployment of such technology to enable real-time monitoring of a surge-type glacier in Svalbard. Kongsvegen, a glacier that last surged in 1948, has started to gradually accelerate in recent years, and a new surge may be imminent. In Spring 2018 we drilled a borehole to the bed of the glacier and installed thermistors and a basal probe to measure water pressure and properties near the bed. The borehole probes were wired to a Campbell logger, which was programmed to output data at 30-minute intervals to a $40 Pycom telemetry chip that runs on open-source python libraries. The Pycom microcontroller reads and parses the borehole data stream, then reads in updated position coordinates from an external GNSS unit mounted on the surface. The data packet is then sent using a long-rage LoRa radio to a wireless gateway located about 10 km away at the glacier pass. The gateway, which is within line-of-sight of a cellular tower 75 km away in Longyearbyen, then transmits the data to a cloud server for immediate access. We share our experience with the development and deployment of this instrumentation, the data received thus far, and plans for integrating telemetry capabilities with existing and planned in-situ monitoring activities at Kongsvegen and elsewhere. Future efforts are aimed at utilizing new python libraries for creating decentralized and adaptive mesh networks for communicating and transmitting data through distributed networks of sensors. In areas without cellular coverage, data from networks of sensors deployed in the field could be retrieved using just a single node with satellite communication capability.