Are snow patterns well modelled when simulating river discharge in Mediterranean mountain catchments? A multimodel approach assessment using remote sensing data

Modelling streamflow in mountainous areas is challenging. The presence of snow is an additional factor to consider, as it is the primary driver of streamflow dynamics in mountain catchments. In addition, this complexity increases in the Mediterranean mountains, where snow dynamics are more variable, with specific characteristics, including shallow snowpack, high density, and evaposublimation rates that cannot be neglected when assessing water resource availability during the dry season. Many approaches, with varying levels of complexity, have been used to model streamflow in mountainous areas. In general, these models are calibrated and evaluated against streamflow without considering their performance with respect to snow dynamics. That is, river discharges are well represented, but not due to the correct reasons.

This study assesses the implications of selecting snow parameterizations for streamflow modelling in Mediterranean mountain catchments, considering not only streamflow but also snow performance. Five different hydrological models, with different conceptualizations – lumped, semi-distributed, and fully distributed – and with different levels of complexity regarding snow parameterization – degree-day, radiation-day, and mass and energy balance approach– have been used. These models are: (1) GR4J associated with CemaNeige (lumped with degree-day snow model), (2) SWAT (semidistributed with degree-day snow model), (3) HYPE (semidistributed with radiation-day snow model), (4) GEOFRAME (semidistributed with temperature-radiation-day snow model), and (5) WiMMed (distributed with mass and energy balance snow model). Models were calibrated against streamflow observations and evaluated for snow performance using remote-sensing-derived snow-cover area. A spectral mixture analysis carried out using Landsat imagery, considering the three main land cover types over the region: snow, shallow vegetation, and rocks, was performed to define the fraction of snow in each cell. The values of these pixels were aggregated at the catchment scale for comparison with the simulations. The Guadalfeo River basin in southern Spain has been selected as representative of a Mediterranean mountain-coastal catchment for this analysis.

Preliminary results indicate that the complexity of snow dynamics is better captured by the more complex approach, namely, the fully distributed mass and energy balance snow model. However, the assessment indicates that simpler approaches can be valid when analyzing changes and seasonality rather than actual values. This observation underscores the potential to use this model in an ensemble to compute hydrological uncertainty, as is common in hydrological seasonal prediction and climate studies.

Acknowledgments: This work is part of the project PCI2024-153496, funded by MCIU/AEI/10.13039/501100011033 and EU