Abstract

In many cold climates, rain-on-snow (ROS) events are associated with severe snowmelt and flooding. ROS events also rapidly deplete snowpacks, reducing the potential for subsurface water storage later in the year. We incorporated a simple, easily transferable energy-balance ROS model into the Soil and Water Assessment Tool (SWAT) to assess how ROS melt affects winter floods and summer hydrological drought over a large area such as the North American Great Lakes Basin, where ROS is associated with severe snowmelt events. Using 504 random parameter sets, the modification consistently improved simulations and led to higher winter flows and lower summer flows compared with the unmodified SWAT. The SWAT ROS model also had improved performance for simulating daily streamflow in 501 (99.4%) of the 504 random parameter sets and improved performance for simulating daily snowpack in 504 (100%) of the sets, compared to the unmodified SWAT. We then used streamflow and snow water equivalent as the objectives in a multivariable, multi-site calibration to compare SWAT ROS with the unmodified SWAT. The SWAT ROS model simulated 51% larger peak (0.95 quantile) daily flows during winter and spring and 58% lower daily summer low (0.05 quantile) flows across the Great Lakes Basin, compared to the unmodified SWAT. We also used observed snowpack data to demonstrate how the unmodified SWAT can miss daily ROS melt events, delaying snowmelt to later in the season. Thus, the unmodified SWAT model appears to be misrepresenting the streamflow distribution in areas where ROS events occur, which is particularly important for modeling extreme events. When simulating conditions in cold climates at diverse scales up to large basins or continents, hydrological models such as SWAT must incorporate ROS, as many other models already do. This has implications for water resources management confronted with hydrological extremes in ROS-prone areas around the world, especially where climate change is altering ROS melt events.

Full Text
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