Snow leopard | EPFL Graph Search

The snow leopard (Panthera uncia), commonly known as the ounce, is a species of large cat in the genus Panthera of the family Felidae. The species is native to the mountain ranges of Central and South Asia. It is listed as Vulnerable on the IUCN Red List because the global population is estimated to number fewer than 10,000 mature individuals and is expected to decline about 10% by 2040. It is mainly threatened by poaching and habitat destruction following infrastructural developments. It inhabits alpine and subalpine zones at elevations of , ranging from eastern Afghanistan, the Himalayas and the Tibetan Plateau to southern Siberia, Mongolia and western China. In the northern part of its range, it also lives at lower elevations. Taxonomically, the snow leopard was long classified in the monotypic genus Uncia. Since phylogenetic studies revealed the relationships among Panthera species, it has since been considered a member of that genus. Two subspecies were described based on morph

Modeling the hydrologic response of snow-dominated Alpine catchments: the role of sunlight exposure

Pierfrancesco Da Ronco

This work investigated how important the explicit modeling of sunlight exposure (aspect, slope) is for discharge simulation in a high alpine catchment. The used spatially-explicit hydrological model includes a simple snow accumulation and melt routine (based on the degree-day method) and simulates discharge at a daily time step. The main conclusion of this work is that the role of sunlight exposure, while being crucial to simulate the hydrological response of individual subcatchments, is averaged out at the catchment scale.

2013

Micromechanical modeling of snow failure

Johan Alexandre Philippe Gaume, Alec van Herwijnen

Dry-snow slab avalanches start with the formation of a local failure in a highly porous weak layer underlying a cohesive snow slab. If followed by rapid crack propagation within the weak layer and finally a tensile fracture through the slab, a slab avalanche releases. While the basic concepts of avalanche release are relatively well understood, performing fracture experiments in the laboratory or in the field can be difficult due to the fragile nature of weak snow layers. Numerical simulations are a valuable tool for the study of micromechanical processes that lead to failure in snow. We used a three-dimensional discrete element method (3-D DEM) to simulate and analyze failure processes in snow. Cohesive and cohesionless ballistic deposition allowed us to reproduce porous weak layers and dense cohesive snow slabs, respectively. To analyze the micromechanical behavior at the scale of the snowpack (∼1 m), the particle size was chosen as a compromise between low computational costs and detailed representation of important micromechanical processes. The 3-D-DEM snow model allowed reproduction of the macroscopic behavior observed during compression and mixed-mode loading of dry-snow slab and the weak snow layer. To be able to reproduce the range of snow behavior (elastic modulus, strength), relations between DEM particle and contact parameters and macroscopic behavior were established. Numerical load-controlled failure experiments were performed on small samples and compared to results from load-controlled laboratory tests. Overall, our results show that the discrete element method allows us to realistically simulate snow failure processes. Furthermore, the presented snow model seems appropriate for comprehensively studying how the mechanical properties of the slab and weak layer influence crack propagation preceding avalanche release.

2020

Upscaling the evolution of snow microstructure

Quirien Eibhilín Krol

Snow microstructure and its evolution play an important role for various applications of snow physics in cryospheric sciences. The main modes of microstructure evolution in snow are referred to as isothermal and temperature gradient metamorphism. The former describes the coarsening driven by interfacial energy while the latter is dominated by recrystallization processes induced by temperature gradients. An accurate description of these processes in snowpack models is of key importance. However common snowpack models are still based on traditional grain metrics, originally tailored to field observations, and empirical evolution laws. This treatment of snow microstructure is essentially unrelated to recent advances of snow observations by microcomputed tomography (ÎŒCT). The present thesis contributes to the solution of this problem by i) identifying suitable microstructure parameters ii) deriving evolution equations for these from first principles and iii) developing methods that allow to utilize 4D ÎŒCT measurements of snow as a link between local ice crystal growth and upscaled microstructure as relevant on the scales of interest for common snowpack models. To this end, three studies have been conducted. The first study focuses on estimating local ice-crystal growth rates from interface tracking by analyzing 4D ÎŒCT data of in-situ snow metamorphism experiments under isothermal and temperature gradient conditions. For temperature gradient metamorphism diffusion-limited growth is considered, while for isothermal metamorphism the data is compared to kinetics and diffusion limited growth. Despite considerable scatter, in both cases the significance of underlying growth laws could be statistically confirmed. The second study uses ÎŒCT images from a variety of snow samples to investigate the role of grain shape in the context of microwave and optical properties of snow. Grain shape can be objectively defined via size-dispersity of structure from the second moment of either the mean curvature distribution or the chord-length distribution. In addition, a quantitative link between these quantities and the exponential correlation length is shown. The latter is relevant for parameterizing macroscopic properties such as microwave scattering coefficients, dielectric permittivity and thermal conductivity. Finally, a rigorous, upscaled microstructure scheme is developed by deriving mathematically exact evolution equations for the density, specific surface area, the mean and Gaussian curvature and the second moment of mean curvature. The microstructural evolution is driven by local ice crystal growth. All parameters are upscaled by volume averaging and the correctness of the model is confirmed for the time evolution of idealized grains. The model can be compared to 4D ÎŒCT data without any a-priori assumptions. This benchmarking reveals the uncertainties of the interface tracking method which are largely caused by limited temporal and spatial resolution. The model allows to statistically assess the validity of ice crystal growth laws during snow metamorphism. For a temperature gradient experiment it is shown that a diffusion limited growth law is not consistent with the observed decay of the specific surface area. The developed model is a powerful and rigorous tool that is tailored to 4D ÎŒCT data. It connects microscale ice-crystal growth thermodynamics with the macroscale snowpack modeling.

EPFL2017

Upscaling the evolution of snow microstructure

Quirien Eibhilín Krol

EPFL2017