Watershed Symposium 2024

Summary:
Dust blowing from dry lakebeds annually darkens the snowpack of the Great Salt Lake Basin. The darkened snow absorbs more sunlight, resulting in earlier snowmelt. Here, we have used a combination of fieldwork, satellite observations, and modeling to quantify the impact of dust snowmelt, in hopes of improving water supply forecasts in the region.

Full Abstract:
Seasonal snow in the Great Salt Lake Basin (GSLB) provides critical water resources for human infrastructure and local ecosystems alike. The GSLB snowpack has a first order influence on water availability to 2.7 million Utahns and provides the main surface inflows to the Great Salt Lake. Snowmelt rates are primarily controlled by snow albedo, which is impacted by surface darkening from light absorbing particles (LAPs). In the Wasatch Mountains, the primary LAP constituent is dust originating from dry lakebeds across the eastern Great Basin. Dust accelerates snowmelt, adding uncertainty to streamflow forecasts. Despite this, the impact of dust on snowmelt timing is not well known in the GSLB and is not directly accounted for in operational models. Here we present three years of research targeted at quantifying the spatial and temporal distribution of dust on snow and its impacts on snowmelt rates and timing across the GSLB. Our work includes a time series of point-based field observations, analysis of 23 years of satellite remote sensing retrievals, and basin distributed process-based snowmelt modeling. Results reveal that dust impacts snowmelt annually, but with high variability year-to-year, and with no strong temporal trends in the last two decades. The annual impact of dust on snowmelt was quantified over two distinctly different water years (2022 and 2023) by running two model implementations with different albedo representations: 1) A standard time decay relationship representing clean snow albedo evolution, and 2) daily remotely sensed observed snow albedo from MODIS. Differences between model runs, evaluated by melt rates, surface water inputs, and snow depletion timing, reflect the influence of snow darkening on snowmelt across the basin. This approach has allowed us to parse out physical drivers of snowmelt and is the first study to quantify snowmelt acceleration due to dust over the GSLB.