ABSTRACT:

This study investigates the dynamics of snowmelt and groundwater storage within the North Alouette River
catchment, using streamflow recession analysis as a novel approach to quantify snowmelt contributions. Initially, a
virtual watershed model is developed to simulate the relationships between temperature, precipitation, and storage
fluxes. This model, based on a storage-discharge method, provides insights into groundwater storage estimation
and the potential to infer snowmelt from discharge data. The method is then applied to the North Alouette River
catchment (BC, Canada), analyzing five years of hydrogeological data. Results indicate seasonal patterns of groundwater storage
and snowmelt, with snowmelt primarily occurring between mid-May and early July. This study acts as a proof of
concept, demonstrating the feasibility of using discharge data to estimate snowmelt through groundwater storage.
Despite promising findings, the study highlights limitations such as the exclusion of evapotranspiration and the
challenges posed by the region’s limited snow coverage. The findings underscore the importance of refining models
to include all relevant hydrological processes, aiming to enhance water resource management in the context of
climate change.