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Mac Beers Thesis Defense

November 17 @ 3:00 pm - 4:00 pm MST

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Title: Climate and channel morphology control stream drying across scales

Abstract: Over half of the global stream network is estimated to dry for at least one day of the year. Streams that dry at some point in space and time are considered intermittent. Intermittent streams exhibit one of three hydrologic states: flowing, non-flowing pools, and dry. The distribution and extent of completely dry channel and non-flowing pools is important for water quality and ecology, however, we are currently unable to accurately predict when, where, and how streams dry at small scales. Few studies have investigated the stream characteristics that influence local scale controls of drying, and more work is needed to quantify and predict intermittency across the stream network. At regional, national, and global scales, climate exerts the greatest influence on stream drying. However, there is limited work investigating how competing climatic forces throughout a water year determine drying, particularly in headwater catchments where drying occurs most. To address these knowledge gaps, this thesis investigates controls of stream drying in the Dry Creek Experimental Watershed (DCEW). At the local scale (1-15m), we find that the onset of drying occurs slowly as base flows decline, and more locations become dry over the intermittent period. Breaks in channel slope create a local drying pattern as the intermittent reach dries; drying occurs first above the break in slope and last at the base of the break in slope. When streamflow returns, the stream quickly reconnects across the intermittent reach, and the return of streamflow is coincident with declining air temperatures and precipitation events in the fall. We also investigate how climate controls stream drying at a continuous monitoring station at the outlet of DCEW. We find that summer evapotranspiration is an indicator of water availability in the DCEW and is strongly correlated with the number of days the stream dries, among other drying metrics. Drying metrics are also strongly influenced by maximum SWE, day of snow full melt, mean spring temperature, and spring precipitation. Finally, we demonstrate that multiple data sources at permanent streamflow monitoring stations can be used to more accurately quantify drying metrics.

Advisors: Anna Bergstrom, Kevin Roche

Committee Members: Jim McNamera, Lejo Flores, Tyler King