DrivenData is a website that hosts machine learning competitions, often involving some component of Earth Science or hydrology. In 2022, they hosted a competition sponsored by the US Bureau of Reclamation to predict snow quantity across the Western US. Although I didn’t have much experience with machine learning at the time, I decided to participate …
Continue reading “Predicting Water Supply – Another Machine Learning Competition”
In my last blog post, I tried to answer the question: How has snowfall at Sandia Peak Ski Area changed over the years? Ultimately, I want to know how climate change is affecting the future of skiing in the Sandias and to develop some sense of what weather patterns are associated with particularly good or …
A few months ago I found out my local ski area, Sandia Peak, preemptively chose not to open for the upcoming ski season (2022/2023). It isn’t that unusual for Sandia Peak to stay closed for the season, and they were also closed last season. However, I had thought the decision to stay closed is typically …
Overview Last winter I tried my hand at competing in a machine learning competition to predict snow water equivalent (SWE) across the Western United States. I learned a lot and created a two part blog series to document both the competition and my approach: Machine Learning for Snow Hydrology – A CompetitionMachine Learning for Snow …
Continue reading “Machine Learning for Snow Hydrology – A Follow Up”
Overview I built a very unusual weather station on my roof. The measurements are pretty standard: wind, temperature, humidity – but everything else is unique, all the way down to the electronics. You can see a subset of the data, updated every 10 minutes at apps.crceanalytics.com/wxstation. It is far from the easiest or cheapest approach …
My graduate degree research was focused on glacial hydrology, which is basically trying to figure out how water moves above, below, and through glaciers and ice sheets. Water is important because it affects things like sliding, melting, sub-glacial erosion, and geochemistry. My research utilized temperature measurements from snow on the Greenland ice sheet, and I …
The mean annual precipitation in NM is about 14 inches which makes it one the driest states in the US. Almost the entire Western US is much drier than the Eastern US, and climate change is likely to make things worse. Water management is therefore critical, and I recently starting interacting with the New Mexico …
I wrote this a few years ago on another blog, but I think it is still relevant so I am re-posting it here. The code is still available on Github. I worked for several years at USU on the iUTAH project. While there I managed a network of water monitoring stations along the Logan river, …
Continue reading “Stream Rating Curves and Jupyter Notebook”
This is the second part of my two part series on a machine learning competition to predict snow water equivalent (SWE). In Part 1, I describe the competition, as well as, my process for coming up with an approach for making SWE predictions at 9,067 locations across the Western US. That approach, sometimes called the …
Continue reading “Machine Learning for Snow Hydrology – Methods”
Part 1: Competition Overview Late last December I ran across a machine learning competition hosted by Driven Data. The goal of the competition is to predict snow water equivalent at high spatial resolution across the western US. I had never before thought of participating in a machine learning competition, although I had heard of the …
Continue reading “Machine Learning for Snow Hydrology – A Competition”
