Temperature Loggers Shed Light on Past and Future Yellowstone Geyser Activity

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Selected hydrothermal features at Yellowstone National Park have data loggers that capture geyser eruption times. A systematic analysis of these data can reveal variations in geyser activity over time and between different geyser basins.

Yellowstone Caldera Chronicles is a weekly column written by scientists and collaborators of the Yellowstone Volcano Observatory. This week's contribution is from C. Nur Schuba, Visiting Scientist with Yellowstone National Park.

Different views of an eruption from two predictable geysers

Different views of an eruption from two predictable geysers. (a, c) Graphs showing water temperatures recorded by data loggers stationed near Beehive and Old Faithful Geysers, respectively. These data loggers were deployed by the Yellowstone Geology Program, configured to capture temperatures at one-minute intervals (indicated by blue dots). Significant upticks in temperature signify eruptions (indicated by red dots). The sawtooth pattern at the base is caused by daily average temperature variations. (b, d) Photos show Beehive and Old Faithful Geysers at the peak of their eruptions. Figure by C. Nur Schuba, Yellowstone National Park.

Since 1994, the Yellowstone Geology Program has maintained an array of temperature data loggers throughout geothermal areas in Yellowstone National Park. This was motivated in part by a federal responsibility to monitor Yellowstone geothermal systems, as well as the desire to create a database that will help better understand geyser activity.

As of late 2021, the Yellowstone Geology Program has deployed 64 temperature loggers. These loggers record temperatures at one-minute intervals, similar to the radio-telemetered network of sensors at Norris Geyser Basin. The main intention behind this effort is to monitor both natural and human-caused changes in hydrothermal activity. Each hydrothermal feature presents a unique dataset and a challenge on how it can be analyzed. Predictable geysers with frequent eruptions, like Old Faithful, yield data that resemble a cardiogram. Just like how different people can have drastically different heartbeat data, temperature data from various predictable geysers can be completely different from one another. As a result, it is difficult to do a one-size-fits-all statistical analysis on all geyser data.

Applying statistical analysis on temperature logger data is not exactly novel. For instance, Yellowstone Resource & Youth Programs do this on a daily basis on predictable geysers in the Upper Geyser Basin to inform visitors on when a certain feature may erupt. A sign near Daisy Geyser, for example, might indicate that it may go off in the next hour (plus or minus 20 minutes), not because there is always somebody watching this geyser and keeping track of its last eruption, but because a park employee utilized data from a temperature logger and created a projection for the next eruption based on its past data.

Example initial analyses on the water temperature data

Example initial analyses on the water temperature data. (a, c) Graphs showing the calculated time between eruptions. (b, d) Histograms demonstrating the distribution of eruption intervals. Given this single week in June, we observe that Beehive Geyser erupted in a bi-modal fashion, preferring ~15 hour and ~19 hour intervals, while Old Faithful shows a unimodal trend with a mean of ~97 minutes. Figure by C. Nur Schuba, Yellowstone National Park.

Similar to this approach, researchers use temperature and seismic data to understand how and why geyser eruption activity might change over time. For example, scientists from the University of Utah and Yellowstone National Park demonstrated that geyser activity can be altered by large-magnitude earthquakes, even if they are far away. In 2002, a 7.9 earthquake in Alaska caused a shortening in eruption intervals at some geysers in the Upper Geyser Basin by more than 30 minutes! These features took over two months to return to their previous eruption intervals, so the changes were temporary. As another example, USGS, Stanford University, and Yellowstone National Park scientists linked climate-induced changes to the geyser eruption activity, showing correlations in average geyser eruption intervals and river discharges over years. One of their key conclusions was on how statistical analysis indicates that geysers respond to both long-term precipitation (rain and snow) trends and to the seasonal hydrologic cycle (wet winters and drier summers).

And this is just for predictable geysers! Most of the geysers in the park are not predictable, but by monitoring their eruption intervals over long periods of time it might be possible to discern some patterns, or their responses to earthquakes or climate conditions. This might help us better understand how and why these geysers erupt, and how they differ from more predictable geysers.

It cannot be stressed enough just how crucial temperature data can be for geyser research at Yellowstone. Understanding how and why changes in predictable geyser behavior occur, determining variations in activity in different geyser basins within Yellowstone, analyzing correlations between climate and (currently) unpredictable geysers, measuring how factors external to the park (like distant earthquakes) affect geyser activity in Yellowstone... all can be aided by the comprehensive temperature data that are being collected by the Yellowstone Geology Program.

Presently, all recorded hydrothermal feature temperature data from Yellowstone National Park loggers are going through a quality assurance process. Approved data will be publicly available on the National Park Service's Integrated Resource Management Applications (IRMA) Portal soon. Stay tuned!

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Norris Geyser Basin is one of the most dynamic geyser basins in Yellowstone National Park. It frequently experiences "disturbances" when thermal activity waxes and wanes and water chemistry changes over the course of a season. Earthquake swarms are common nearby, and the surface moves up and down with some regularity.