Wed. Sep 28th, 2022
Flooding in Midland, Michigan, in May 2020 after heavy rains caused the failure of two dams.
enlarge Flooding in Midland, Michigan, in May 2020 after heavy rains caused the failure of two dams.

Climate change has direct consequences for the water cycle through our environment. The warmer atmosphere holds more moisture, causing heavy rains to drain even more water than before. On the other hand, warmer air through evaporation can suck even more moisture from the soil, exacerbating droughts. These things should obviously lead to changes for streams. But the amount of water in streams varies wildly under normal conditions, and it can also be affected by more than just the weather. Finding trends in that data has proven difficult.

A new study led by Evan Dethier of Dartmouth College aimed to group streams into physically meaningful categories, to see if consistent patterns emerge once apples are separated from oranges. That analysis reveals some trends — both in high-current extremes and low current.

Go with the flow

Many efforts have found mixed trends between flows when analyzing records of annual peak flows, where records tend to go back further than constant measurements. Attempts to look for regional patterns are largely based on grouping by arbitrary cadres or political boundaries, which have only a limited connection to the landscape.

The new research included about 540 power stations in the US and Canada, all from low-human impact locations that have at least 60 years of data. To place the stations in groups, they used their location, elevation, and seasonal flow pattern. The sites were clustered into 15 different groups, 12 of which had a large enough number of stations to attempt a trend analysis with.

These groups were analyzed for changes in the frequency of extremely high and low discharge on an annual and seasonal scale. The researchers calculated this for events of varying rarities (50 percent probability per year, 20 percent probability per year, etc.) and from different starting years, but the results were generally consistent.

There are two broad themes that stand out from the results: one for areas where snowmelt is causing the peak flows, and another for areas where drought is prevalent. The snowmelt regions include the Pacific Northwest, Rockies (both in the US and Canada), Midwest, Appalachians, and Northeast. In these places there is either a trend towards higher peak flows in the spring or higher peak flows in the winter. This is consistent with the trend towards earlier snow cover depletion with rising spring temperatures.

Separately, high currents in the summer and fall are more common in the Northeast, Midwestern and Appalachian regions, matching the precipitation trends.

Changes in extremes by season (quarter of circles) for each region.  Darker colors represent the highest statistical confidence.
enlarge Changes in extremes by season (quarter of circles) for each region. Darker colors represent the highest statistical confidence.

dry out

In the areas that are often subject to drought – the west coast and the southern stratum of the country – power flow trends look different. An increased frequency of low-flow summer and fall events is common everywhere, with West Coast areas also seeing more high-flow events. The researchers point out that low-current events caused by drought are generally regional in scale, which makes them stand out in the analysis. In contrast, storm-driven high-flow events are much more localized. But with a large enough data set, those trends can also become apparent.

Where regions show statistically significant trends, the researchers say, the mean change is a doubling of the frequency of that type of streamflow event since 1950.

By better grouping similar flows, this method helps unravel the impact of climate trends on the blue ribbons that connect the North American landscape. That means more actionable information on a local scale. And as the researchers put it, “Decisions regarding extreme high- and low-flow river events have multibillion-dollar consequences.”

Science Advances, 2020. DOI: 10.1126/sciaadv.aba5939 (About DOIs).

By akfire1

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