Regional Mountain Conference

This work presents an application of the GEOframe hydrological modeling system to the Sesia River basin, within the broader framework of hydrological assessment in the Po River District. The Sesia catchment represents a paradigmatic example of Alpine river systems, characterised by pronounced altitudinal gradients, extensive snow-dominated headwaters, residual glacierised areas, and highly anthropised lowland sectors. These features make it particularly suitable for investigating the interactions between cryospheric processes, climate variability, and downstream water availability, and for serving as a representative case study for Alpine catchments within the Po River District.
The study focuses on the calibration of the snow module of GEOframe using the high-resolution Snow Water Equivalent (SWE) dataset produced by Dall’Amico et al. (2025). This snow-oriented calibration is first conducted independently and subsequently analysed in terms of its influence on the estimation of other model components parameters governing soil water dynamics, evapotranspiration, and runoff generation. Model performance is assessed through systematic comparisons between simulated and observed river discharge at the main hydrometric stations within the basin.
Special attention is devoted to the hydrological years 2021–2023, which were characterised by severe water scarcity and prolonged drought conditions across Northern Italy, partly driven by persistent snow droughts and anomalous melt dynamics. These years provide a critical test period for evaluating model robustness under extreme hydroclimatic stress.

To quantify the added value of snow-informed calibration, two modeling configurations are compared: a model calibrated jointly on SWE and discharge observations, and a model calibrated exclusively on discharge data. Simulations for the period 2021–2023 are then analysed in terms of accuracy, and predictive reliability.
The comparison enables an assessment of how improved representation of snow processes affects the overall water balance, particularly during dry periods, contributing to a better understanding of parameter interdependencies and highlighting the central role of cryospheric information for enhancing hydrological modeling in Alpine environments. Moreover, this study will provide scientifically robust support for the development and updating of the Water Balance Plan (PBI) of the Po River Basin District Authority, contributing to more informed and adaptive water planning strategies.