Ariana Smith

Project

Evaluating a novel rainfall-runoff event identification method – A case study of the Bow at Banff basin

Short Bio

Ariana is a recipient of the Dean’s Research Award (DRA) for both Fall 2024 and Winter 2025. In Fall 2024, her research focused on evaluating a novel, objective approach for identifying rainfall-runoff events: the Detrending Moving-Average Cross-Correlation Analysis–Event Separation Routine (DMCA-ESR), developed by Giani et al. (2021, Water Resources Research). She applied this method to the Bow River Basin at Banff, comparing the detected rainfall and runoff events with observed data to assess the method’s performance. Through this work, Ariana developed strong skills in data analysis and programming, contributing valuable insights into flood generation mechanisms and advancing the understanding of hydrological processes.

In Winter 2025, Ariana extended her work by refining the DMCA-ESR method for use in cold regions. She tested three temperature-based snowmelt methods and integrated the Modified Degree Day Method into DMCA-ESR to support snowmelt-driven runoff detection. This refined approach was again applied to the Bow River Basin at Banff. The results demonstrated that DMCA-ESR, enhanced with the Modified Degree Day Method, can effectively identify rainfall-runoff events in cold environments.

Ariana’s exceptional contributions were recognized at both the Fall 2024 and Winter 2025 DRA events, where she received the Outstanding Research Performance award twice. Congratulations to Ariana on this well-deserved recognition!