Loading…
Loading grant details…
| Funder | European Commission |
|---|---|
| Recipient Organization | Norges Teknisk-Naturvitenskapelige Universitet Ntnu |
| Country | Norway |
| Start Date | Nov 01, 2022 |
| End Date | Oct 31, 2025 |
| Duration | 1,095 days |
| Number of Grantees | 2 |
| Roles | Associated Partner; Coordinator |
| Data Source | European Commission |
| Grant ID | 101063373 |
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.
Montana State University Bozeman; Norges Teknisk-Naturvitenskapelige Universitet Ntnu
Complete our application form to express your interest and we'll guide you through the process.
Apply for This Grant