Estimating snowmelt contributions to groundwater storage using streamflow recession analysis

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.