Developing Low-Cost Arduino-Based Snowpack Sensing Stations on Mountain Slopes to Improve Flooding and Avalanche Risk Assessment

The snowpack in the White Mountains of New Hampshire and Maine poses threats to backcountry skiers and climbers in the form of avalanches and to people and infrastructure at lower elevations in the form of flooding. Recent spring and winter rain-on-snow flooding events in New Hampshire (January 2019, April 2017, April 2013) highlight the seriousness of the flooding threat, which is likely to persist or increase in frequency. Monitoring how much snow exists on mountain slopes is a huge challenge; the snowpack depth, water content, and temperature can vary significantly over short distances along a single slope. Recent technological advancements in miniaturized less expensive environmental sensors now makes monitoring of the snowpack at high spatial resolution practical.

The first step toward developing a low-cost, in-situ snowpack monitoring platform was taken during the 2018-19 cold season on the lower eastern slope of Mount Washington, New Hampshire (1917 m asl). Six snowpack sensing stations were designed, built, deployed and maintained along the popular Tuckerman Ravine and Sherburne Trails in pairs at three elevations (~750, 1075 and 1200 m asl) by Plymouth State University faculty, staff, students and Mount Washington Observatory staff. Each station contained thermistors spaced at 20 cm from the ground up to 200 cm and at 2 and 10 cm deep in the ground. Each station had a sonic sensor to measure snow depth. A Mayfly microcontroller, powered by a lithium ion battery and solar panel, was programmed to record observations from these sensors every 15-min. The snowpack station data and manual snow water equivalent (swe) measurements at each station collected every 1-2 weeks were sent to the National Weather Service’s Northeast River Forecast Center and National Operational Hydrologic Remote Sensing Center to improve and validate river stage forecasts, airborne swe measurements, and snowpack evolution. The outcomes of this first year of snowpack monitoring serve as a stepping stone to developing a snow energy balance model and the next version of snowpack sensing station being developed for deployment for the 2019-20 cold season that will include radios for a real-time data stream.