With summer just underway here in North America, it may seem like a strange time to talk about snow. But when you live in North Idaho, winter is never very far away and is always very much on everyone’s mind. Our summers are fierce but all too brief, so starting around September, most of us begin to cast a wary eye at the peaks of the Bitterroot range in the mornings, looking for the first signs of snow. And in the late spring, we do much the same, except longingly looking for the first signs that the snowpack is finally breaking up.
We all know how important snow is, of course. Snow is our lifeline, nearly the only source of drinking water we have here, as well as the foundation of our outdoor recreation industries. We also know that the snowpack determines our risk for wildfires, so while the long, dark winters may take a psychological toll, the longer the snow stays on the mountains, the less chance we have of burning come summer.
These are all very subjective measures, though, and there’s way too much riding on the snowpack to leave it up to casual observation. To make things more quantitative, the US Department of Agriculture’s Natural Resources Conservation Service (NRCS) has built a system across the western US that measures the snowpack in real-time, and provides invaluable data to climatologists, fish and game managers, farmers, and even the recreation industry, all of whom have a vested interest in the water held within. The network is called SNOTEL, and I recently got a chance to take a field trip with a hydrologist and get an up-close look at how it works.
Continue reading “Know Snow: Monitoring Snowpack With The SNOTEL Network”
The architecture is quite straightforward. The ESP32 based sensor nodes publish their readings to an MQTT broker running on the Raspberry Pi. The Pi subscribes to these sensor node topics to pick up the relevant sensor data. This makes it easy to add additional sensor nodes in future. Weather forecast data is collected by connecting to the OpenWeatherMap API. All of the collected information is then displayed through an app built using the Kivy: open source Python app development framework. 
with simple 4-way I2C connectors. Temperature, humidity, and pressure are handled by a BME280 module, UV Index (SI1145), visible light (BH1750) even soil humidity and temperature with a cable-mounted SHT10 module.
