Wind‐blown sand is the main driver of dune development and dust emission from soils and is thus of fundamental importance for geomorphology, ecology, climate, and air quality. Even though sand transport is driven by nonstationary turbulent winds, and is thus inherently intermittent, current parameterizations in atmospheric models assume stationary wind and continuous transport. We draw on extensive field measurements to show that neglecting saltation intermittency causes biases in the timing and intensity of predicted fluxes. We present a simple parameterization that accounts for saltation intermittency and produces substantially improved agreement against measurements. We investigate the implications of accounting for transport intermittency in atmospheric models by analyzing 35 years of hourly wind speed data from climate simulations. We show that accounting for intermittency leads to significantly different predictions of sand mass fluxes throughout the year, with potential implications for timing and intensity of dust emission.

The wind‐driven saltation of granular material plays a key role in various geophysical processes on Earth, Mars, Venus, and Titan. Although interparticle cohesion is known to limit the number of grains lifted from the surface through aerodynamic entrainment and granular splash, the role of cohesion in the development of saltation from onset to steady state is still poorly understood. Using a numerical model based on the discrete element method, we show that saltation over cohesive beds sustains itself at wind speeds 1 order of magnitude smaller than those necessary to initiate it, giving rise to hysteresis in which the occurrence of transport depends on the history of the wind. Our results further suggest that saltation over cohesive beds requires much longer distances to saturate, thereby increasing the size of the smallest stable bed forms. These findings have implications for dune formation, dust emission, and snow sublimation over cohesive beds.

Despite being the main sediment entrainment mechanism in aeolian transport, granular splash is still poorly understood. We provide a deeper insight into the dynamics of sand and snow ejection with a stochastic model derived from the energy and momentum conservation laws. Our analysis highlights that the ejection regime of uniform sand is inherently different from that of heterogeneous sand. Moreover, we show that cohesive snow presents a mixed ejection regime, statistically controlled either by energy or momentum conservation depending on the impact velocity. The proposed formulation can provide a solid base for granular splash simulations in saltation models, leading to more reliable assessments of aeolian transport on Earth and Mars.

This paper presents a spatially explicit model for hydrothermal response simulations of Alpine catchments, accounting for advective and nonadvective energy fluxes in stream networks characterized by arbitrary degrees of geomorphological complexity. The relevance of the work stems from the increasing scientific interest concerning the impacts of the warming climate on water resources management and temperature-controlled ecological processes. The description of the advective energy fluxes is cast in a travel time formulation of water and energy transport, resulting in a closed form solution for water temperature evolution in the soil compartment. The application to Alpine catchments hinges on the boundary conditions provided by the fully distributed and physically based snow model Alpine3D. The performance of the simulations is illustrated by comparing modeled and measured hydrographs and thermographs at the outlet of the Dischma catchment (45 km 2 ) in the Swiss Alps. The Monte Carlo calibration shows that the model is robust and that a simultaneous fitting of streamflow and stream temperature reduces the uncertainty in the hydrological parameters estimation. The calibrated model also provides a good fit to the measurements in the validation period, suggesting that it could be employed for predictive applications, both for hydrological and ecological purposes. The temperature of the subsurface flow, as described by the proposed travel time formulation, proves warmer than the stream temperature during winter and colder during summer. Finally, the spatially explicit results of the model during snowmelt show a notable hydrothermal spatial variability in the river network, owing to the small spatial correlation of infiltration and meteorological forcings in Alpine regions.

Abstract. Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

Preferential deposition of snow and dust over complex terrain is responsible for a wide range of environmental processes and accounts for a significant source of uncertainty in the surface mass balances of cold and arid regions. Despite the growing body of literature on the subject, previous studies reported contradictory results on the location and magnitude of deposition maxima and minima. This study aims at unraveling the governing processes of preferential deposition in a neutrally stable atmosphere and to reconcile seemingly inconsistent results of previous works. For this purpose, a comprehensive modeling approach is developed, based on large eddy simulations of the turbulent airflow, Lagrangian stochastic model of particle trajectories, and immersed boundary method to represent the underlying topography. The model is tested against wind tunnel measurements of dust deposition around isolated and sequential hills. A scale analysis is then performed to investigate the dependence of snowfall deposition on the particle Froude and Stokes numbers, which fully account for the governing processes of inertia, flow advection, and gravity. Model results suggest that different deposition patterns emerge from different combinations of dimensionless parameters, with deposition maxima located either on the windward or the leeward slope of the hill. Additional simulations are performed, to test whether the often used assumption of inertialess particles yields accurate deposition patterns. Results indicate that this assumption can be justified when snowflakes present dendritic shape but may generate unrealistic results for rounded particles. We finally show that our scale analysis provides qualitatively similar results for hills with different aspect ratios.

Solar radiation is a dominant driver of snowmelt dynamics and streamflow generation in alpine catchments. A better understanding of how solar radiation patterns affect the hydrologic response is needed to assess when calibrated temperature‐index models are likely to be spatially transferable for ecohydrological applications. We induce different solar radiation patterns in a Swiss Alpine catchment through virtual rotations of the digital elevation model. Streamflow simulations are performed at different spatial scales through a spatially explicit hydrological model coupled to a physically based snow model. Results highlight that the effects of solar radiation patterns on the hydrologic response are scale dependent, i.e., significant at small scales with predominant aspects and weak at larger scales where aspects become uncorrelated and orientation differences average out. Such scale dependence proves relevant for the spatial transferability of a temperature‐index model, whose calibrated degree‐day factors are stable to different solar radiation patterns for catchment sizes larger than the aspect correlation scale.

Abstract. The Thorpe and Mason (TM) model for calculating the mass lost from a sublimating snow grain is the basis of all existing small and large-scale estimates of drifting snow sublimation and the associated snow mass balance of polar and alpine regions. We revisit this model to test its validity for calculating sublimation from saltating snow grains. It is shown that numerical solutions of the unsteady mass and heat balance equations of an individual snow grain reconcile well with the steady-state solution of the TM model, albeit after a transient regime. Using large-eddy simulations (LES), it is found that the 5 residence time of a typical saltating particle is shorter than the period of the transient regime, implying that using the steady state solution might be erroneous. For scenarios with equal air and surface temperatures, these errors range from 26% for low-wind low-saturation conditions to 38% for high-wind high-saturation conditions. With a small temperature perturbation of 1 K between the air and the snow surface, the errors due to the TM model are already as high as 100% with errors increasing for larger temperature perturbations.