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  • Writer's pictureNikki

Wild and scenic: How the Yampa River flows

The Yampa River is the heartbeat of the valley.

Its cadence is almost invisibly slow: one resonating beat per year, reaching its apex in late spring as snow fields spill off the Continental Divide, wind their way down rocky canyons and swell the Yampa over its banks. In the fall and winter, it thins to a quiet trickle, baring its bones to collect snowflakes.

The rhythm of a free-flowing river is unlike its dammed sisters. To live at the whim of a natural hydrograph is to see the reflection of droughts and climate change, weather and snowfall in every drop of water that passes under the Fifth Street Bridge. The last free-flowing river in the Colorado River basin, and a designated Wild and Scenic River, the Yampa holds a particular sanctity, and somewhat of a magical spell over the valley it feeds.

This month, I'm sharing an interactive visualization of Yampa River flows for the past 40 years based on USGS stream flow data from the station in downtown Steamboat Springs. USGS keep extremely detailed records of flows, but it's hard to access all the data in one place. A stripped-down visualization of the patterns and pulses of the Yampa's rhythm year-over-year gives us a more simplistic perspective, reflective of how we experience the Yampa, without all the scientific jargon and technical graphs.

Visit the full visualization here. Enjoy perusing the chart, recognizing the comforting patterns and picking up the anomalies - the late melt-offs, the odd fall rainstorms. Perhaps compare a hydrograph to the patterns of that year's snowfall with the Snow Stripes app.

Learn data science fundamentals by

following along with this post

DATASET: USGS stream flow data


LEARN: dataRetrieval (loading USGS data

directly into R), interactive Plotly charts


The Details

The timing of this month's visualization was tidy - this week is clearly marking the end of a fleeting and meager season of watersports on the river, and a stark reminder of the region's mega-drought. But another impetus for this particular post was the workflow I came across to dive into these data: the R package that chopped off an immensely satisfying amount of clicks from my past efforts with USGS data. Using dataRetrieval, a package created and maintained by USGS scientists, you can access the vast cache of USGS hydrologic data directly from R (don't worry Python folks, they made one for you too!). It's as easy as a few lines of code.

If working with these data constitutes your career, you might already know all of this. But for casual data hobbyists, professors, and students, this package will help you simplify workflows and leave more time for to hone visualization techniques and dive deeper into analyses. Check out the full tutorial here.

Check back for the next post on July 13*.

*I'm off by approximately a week from my planned schedule of posting the first Tuesday of every month. Consider these dates estimates while I'm finishing my dissertation.



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