Class
Article
College
College of Science
Department
Mathematics and Statistics Department
Faculty Mentor
Brennan Bean
Presentation Type
Poster Presentation
Abstract
Given Nevada’s history of destructive flooding resulting from rain falling on mountainous snowpack, often called rain-on-snow (ROS) events, there is a great need to incorporate these events and their residual effects in infrastructure design methods. Examining relationships between USGS streamflow measurements and climate variables (specifically precipitation, temperature, and snowpack) obtained from neighboring SNOTEL stations provides means by which to classify ROS-induced floods from ROS events. Using both temperature and snowpack-based criterion to classify ROS events, this project differentiates between non-ROS and ROS-induced floods in a subset of USGS stations across the Sierra Nevada and reveals that ROS-induced floods produce, on average, significantly higher runoff than their counterparts. Future applications of these results include relating these streamflow findings to precipitation-based and next-generation intensity duration frequency curves to create statistical models that highlight increases of flood likelihood and promote appropriate infrastructure design in areas subject to ROS-induced floods.
Location
Logan, UT
Start Date
4-12-2023 11:30 AM
End Date
4-12-2023 12:30 PM
Included in
Here Come the Floods: Classification of Rain-On-Snow Induced Flooding in Nevada
Logan, UT
Given Nevada’s history of destructive flooding resulting from rain falling on mountainous snowpack, often called rain-on-snow (ROS) events, there is a great need to incorporate these events and their residual effects in infrastructure design methods. Examining relationships between USGS streamflow measurements and climate variables (specifically precipitation, temperature, and snowpack) obtained from neighboring SNOTEL stations provides means by which to classify ROS-induced floods from ROS events. Using both temperature and snowpack-based criterion to classify ROS events, this project differentiates between non-ROS and ROS-induced floods in a subset of USGS stations across the Sierra Nevada and reveals that ROS-induced floods produce, on average, significantly higher runoff than their counterparts. Future applications of these results include relating these streamflow findings to precipitation-based and next-generation intensity duration frequency curves to create statistical models that highlight increases of flood likelihood and promote appropriate infrastructure design in areas subject to ROS-induced floods.