SnowMagnet · Low capillary number flow in phase change porous media: permeability and liquid water capacity of snow.
Horizon Europe — Marie Skłodowska-Curie Actions
- Duration
- 2022-11-01 → 2025-10-31
- EU contribution
- €307,940
- Participants
- 2
- Scheme
- HORIZON-TMA-MSCA-PF-GF
Lines connect the coordinator with its partners.
Results in brief
Low capillary number flow in phase change porous media: permeability and liquid water capacity of snow.
The movement of water through snow is a key factor in seasonal flooding and glacier hydrology, yet its behavior varies significantly due to the complex microstructure of snow. This variability spans several orders of magnitude and is poorly understood, particularly in unsaturated flow conditions. Existing models struggle to accurately represent water transport in snow because they lack a fundamental understanding of pore-scale mechanisms, including liquid water displacement, diffusion, and phase transitions. The SnowMagnet project aims to address these gaps by pioneering nuclear magnetic resonance (NMR) imaging studies on wet snow at the pore scale, a method that overcomes the limitations of micro-computed tomography for transient flow conditions. By combining NMR with Lattice-Boltzmann simulations and Pore-Network models, the project will provide quantitative insights into local saturation dynamics, capillary-driven flow, and hydraulic conductivity across different snow microstructures. A key experimental approach involves 3D-printed porous media, including precisely replicated snow geometries, to refine measurement techniques and validate models before applying them to real snow samples. These controlled experiments, coupled with simulations, will generate high-resolution datasets on unsaturated flow as a function of the capillary number. This data will be instrumental in calibrating dynamic pore-network models, enabling the development of improved constitutive laws and a new parameterization of effective hydraulic conductivity for snow. By resolving water transport mechanisms at the pore scale and linking them to macroscopic flow behavior, the project will establish a new standard for snow hydrology models. This advancement will enhance predictions of snowmelt behavior, contributing to better flood forecasting, glacier mass balance assessments, and hydrological modeling in cold-region environments.
Data: CORDIS, © European Union
Project objective
The effective hydraulic conductivity of snow is highly impacted by its microstructure, introducing a variability of at least three orders of magnitude, impacting seasonal flooding and glacier hydrology. Yet, the mechanisms of unsaturated flow and the impact of local phase transitions have never been investigated at the pore scale. This inhibits improving on the constitutive laws for larger scale models of snow hydrology using upscaling methods. Micro computer tomography is a very effective method for dry snow metamorphism but fails for wet snow because the transient flow and the accelerated change in microstructure cannot be resolved. We propose nuclear magnetic resonance (NMR) methods in combination with Lattice-Boltzmann simulations and Pore-Network models to characterize water flow in snow. Applying these methods on unsaturated flow in snow, we can resolve local saturation, liquid water displacement probabilities and diffusion measures, quantitatively measuring mechanisms of water transport. These are essential for gauging modelling approaches of transport phenomena. Whilst NMR methods have been used extensively on saturated flow, it has found limited application in unsaturated media and is poised for significant advances. To target melt and percolation phenomena in snow, we start with 3D printed porous media (single pores and fully resolved snow geometries) to refine the experimental setup and provide novel data for unsaturated flow in porous media. Assisted by Lattice-Boltzmann simulations we can link pore-scale mechanisms to the NMR data. The action will produce unique data sets on unsaturated flow as a function of capillary number in model porous media and snow. This data will be used to calibrate dynamic pore network models aiming at quantifying the transient flow in snow. This leads to a parameterization of effective hydraulic conductivity for a wide range of snow microstructures providing a new standard for models resolving water transport in snow.
Original text from CORDIS.
Participants
- NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU · TrondheimCoordinatorNorway
- Montana State University Bozeman · BozemanUnited States
Links
- View on CORDIS
- DOI: 10.3030/101063373
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5fb491129&appId=PPGMS
Data: CORDIS, © European Union