A new method for retrieving high spatial resolution snowpack height and water equivalent

Snow plays a fundamental role in the water cycle. In some areas, precipitation in the form of snow and the formation of a seasonal snow cover in the mountains is the main source of freshwater. Snow, accumulated during the winter, supplies drinking water during the spring by quenching the prolonged summer drought of mediterranean regions.

 

There are several methods for measuring snow, some of which are based on measuring the distance from a certain elevation to the ground. This distance can be used to infer the height of the snow cover. To measure this distance, ultrasound or lasers are used. These systems are usually expensive and require infrastructure, both to support the sensors and to be powered by solar panels during the winter. These systems sometimes suffer from operational, structural or energy problems. On the other hand, there are rudimentary manual techniques based on the introduction of probes that determine the distance to the ground in a very robust and simple way. It is also possible to extract samples for density calculation in trenches specifically dug for that purpose. These manual techniques are inexpensive, highly robust, but require human intervention for their operation, therefore, the spatial and temporal density is low.

 

For several years, techniques have been employed to ascertain the height of the snowpack by analyzing temperature data collected at varying heights. These systems, commonly referred to as snow poles, combine the benefits of manual methods, particularly their simplicity, with those of automatic methods, such as their higher temporal resolution. Additionally, they offer further advantages, including their low cost and minimal environmental impact, which allow for a greater density of measurement points to be obtained. This is particularly crucial in complex terrain like mountains. This work presents the methods used to obtain not only the height of the snowpack, but also its equivalent in water using this type of snow pole. Obtaining the water content is especially important and novel in this field. Furthermore, it presents the evolution of the traditional snow pole with several enhancements related to new IoT hardware available. Also, sensitivity tests in the laboratory, network operation and mesh design results will be shown.