H225-05
Drivers of spatiotemporal heterogeneity in precipitation, snowpack storage, and surface water inputs at the rain-snow transition in water-limited western US mountains

Thursday, 17 December 2020: 05:42
Virtual
Sarah Godsey1, Katherine Hale2, Scott Havens3, Danny G Marks3, Patrick Kormos4, Ernesto Trujillo3, Andrew R Hedrick3, Clarissa Lise Enslin5, Adam H Winstral6, Jim P McNamara7 and Timothy E Link8, (1)Idaho State University, Department of Geosciences, Idaho Falls, ID, United States, (2)University of Colorado Boulder, Boulder, CO, United States, (3)USDA-ARS, Northwest Watershed Research Center, Boise, ID, United States, (4)National Weather Service Salt Lake City, Salt Lake City, UT, United States, (5)Idaho State University, Geosciences, Pocatello, ID, United States, (6)WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland, (7)Boise State Univ, Boise, ID, United States, (8)University of Idaho, Water Resources Program, Moscow, ID, United States
Abstract:
The rain-snow transition zone in the western mountains of the United States is hydrologically sensitive to small atmospheric changes because temperatures often hover near the freezing point of water, potentially changing the snow fraction of precipitation. During storms, that snow fraction is also subject to wind redistribution much more than the rain fraction, implying that temperature changes may affect spatial heterogeneity of snowpacks at the rain-snow transition. As heterogeneous snowpacks melt seasonally or episodically during rain-on-snow events, the combination of melt and rain — known as surface water inputs (SWI) — may substantially differ from precipitation. However, predicting spatiotemporal patterns of SWI remains difficult because of these complex interactions between snow fraction, wind redistribution, and rain-on-snow events. To understand the drivers of spatiotemporal patterns of SWI in wet and dry years, we modeled detailed snowmelt dynamics in a small semi-arid watershed located at the rain-snow transition, Johnston Draw at the Reynolds Creek Experimental Watershed and Critical Zone Observatory in southwestern Idaho. We found that annual SWI are more spatially homogeneous in dry years than wet years. Furthermore, annual precipitation drives spatial patterns of SWI, and regardless of the precipitation phase, precipitation magnitude overwhelms snowpack or subsurface storage as a driver of SWI at the annual scale. However, at the event scale, SWI are nonlinearly related to snowpack storage rather than precipitation or subsurface storage. Future modeling of differences in snow fraction between years will help assess changes in streamflow and evapotranspiration associated with future warming, but our modeling results between wet and dry years reveal interactions between precipitation and snowpack storage at different scales at the rain-snow transition in mountainous headwaters.