Rain-on-snow events can lead to an intensification of late summer hydrological drought in Great Lakes watersheds

Abstract:

Rain-on-snow (ROS) events can lead to significant flooding throughout the world. Most hydrologic models, however, do not include ROS events in their modeling framework, leading to a lack of capability to simulate large hydrologic events. Further, a greater export of water from rain-on-snow events during the spring has the potential to reduce subsurface water storage later in the summer. Here, we incorporate an energy balance ROS methodology within the Soil and Water Assessment Tool (SWAT) watershed model. We test this new routine using a SWAT model developed for the Great Lakes Basin in North America, where ROS events have led to catastrophic flooding. Within the Great Lakes Basin, snowfall and snowmelt characteristics can vary tremendously due to lake effects. To account for this variability, we developed a new procedure using multivariable calibration of streamflow and snow water equivalent (SWE) data to more accurately simulate ROS using SWAT. Compared to the default model without ROS methodology, results show that the ROS modification of SWAT results in a larger amount of simulated snowmelt during February (+5.2 mm, 87%) and March (+11.5 mm, 48%) as rainfall is melting more snow, as well as a decrease in streamflow amount during the summer months of July (-2.9 m³s^-1, -24%) and August (-2.0 m³s^-1, -22%) largely due to reduced groundwater baseflow. This suggests that the traditional SWAT model could be underestimating the severity of winter floods and summer droughts in areas where rain-on-snow events occur. Hydrological models need to incorporate ROS so that the effects of these hydrologic events are captured, particularly as climate change is affecting ROS patterns around the globe, causing important implications for water resources management.