- 1C3A - Center Agriculture Food Environment, University of Trento, San Michele all’Adige (TN), Italy (johnn.nith@gmail.com)
- 2Institute for Alpine Environment, EURAC Research Bolzano, Italy
- 3Technology Transfer Centre, Fondazione Edmund Mach, San Michele all’Adige (TN), Italy
- 4Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy
In the European Alps, seasonal snow plays a crucial role in hydrology, functioning as a reservoir by storing precipitation during winter and releasing it during the summer. Snow is highly sensitive to climate change, particularly in low- and mid-elevation mountain regions like the European Alps. In snow-fed basins, any changes in snowmelt contribution to river discharge can significantly impact agriculture, domestic water supply, and hydro power generation.
Hydrological modeling employs a variety of models, ranging from simple lumped models to physically-based, spatially distributed models, to simulate river discharge. These models either have a simple temperature-based or a physically based snow module to simulate the snow dynamics. Distributed, physically based models can provide accurate insights into snow dynamics. However, their high input data requirement, overparameterization, and high computational demands make them challenging to use for operational purposes. In contrast, simple lumped models require less input data, standard snow parameters and are well-suited for operational applications.
In this study, we present an approach to improve both runoff forecasting and spatial snow pattern estimation by integrating the snow water equivalent (SWE) simulations from a physically based GEOtop model into the lumped GEOframe system. We evaluate and compare different approaches, ranging from direct substitution to a mass-conserving statistical downscaling method. The methodology is applied in the Non Valley catchment, Italy, where water is important for agriculture, hydropower, and other uses.
Our initial results from 01-01-2017 to 15-09-2022 at hourly time step show that the GEOframe is able to simulate the discharge very well with a Kling-Gupta Efficiency (KGE) value of 0.87 and 0.72 during the calibration and validation, respectively. This approach aims to preserve the computational efficiency and feasibility of lumped models while incorporating the improved physical representation of snow processes and spatial variability from a physically-based snow model.
Acknowledgement
The work of J.M.W. has been funded by Fondazione CARITRO Cassa di Risparmio di Trento e Rovereto, grant number 2022.0246.
How to cite: Wani, J. M., Bertoldi, G., Bozzoli, M., Andreis, D., and Rigon, R.: Integrating snow-water equivalent simulated by a physically based model into a lumped model in an Alpine catchment in Italy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12258, https://doi.org/10.5194/egusphere-egu25-12258, 2025.
