Accurate snow depth observations are critical to assess water resources. More than a billion people rely on water from snow, most of which originates in the Northern Hemisphere mountain ranges. Yet, remote sensing observations of mountain snow depth are still lacking at the large scale. Here, we show the ability of Sentinel-1 to map snow depth in the Northern Hemisphere mountains at 1 km² resolution using an empirical change detection approach. An evaluation with measurements from ~4000 sites and reanalysis data demonstrates that the Sentinel-1 retrievals capture the spatial variability between and within mountain ranges, as well as their inter-annual differences. This is showcased with the contrasting snow depths between 2017 and 2018 in the US Sierra Nevada and European Alps. With Sentinel-1 continuity ensured until 2030 and likely beyond, these findings lay a foundation for quantifying the long-term vulnerability of mountain snow-water resources to climate change.

ABSTRACT. The spatial pattern of accumulation rate can be inferred from internal layers in glaciers and ice sheets. Non-dimensional analysis determines where finite strain can be neglected ('shallow-layer approximation') or approximated with a local one-dimensional flow model ('local-layer approximation'), and where gradients in strain rate along particle paths must be included ('deep layers'). We develop a general geophysical inverse procedure to infer the spatial pattern of accumulation rate along a steady-state flowband, using measured topography of the ice-sheet surface, bed and a 'deep layer'. A variety of thermomechanical ice-flow models can be used in the forward problem to calculate surface topography and ice velocity, which are used to calculate particle paths and internal-layer shapes. An objective tolerance criterion prevents over-fitting the data. After making site-specific simplifications in the thermomechanical flow algorithm, we find the accumulation rate along a flowband through Taylor Mouth, a flank site on Taylor Dome, Antarctica, using a layer at approximately 100 m depth, or 20% of the ice thickness. Accumulation rate correlates with ice-surface curvature. At this site, gradients along flow paths critically impact inference of both the accumulation pattern, and the depth-age relation in a 100 m core.

[1] Contributions to sea level rise from rapidly retreating marine-terminating glaciers are large and increasing. Strong increases in iceberg calving occur during retreat, which allows mass transfer to the ocean at a much higher rate than possible through surface melt alone. To study this process, we deployed an 11-sensor passive seismic network at Columbia Glacier, Alaska, during 2004Alaska, during -2005. We show that calving events generate narrow-band seismic signals, allowing frequency domain detections. Detection parameters were determined using direct observations of calving and validated using three statistical methods and hypocenter locations. The 1-3 Hz detections provide a good measure of the temporal distribution and size of calving events. Possible source mechanisms for the unique waveforms are discussed, and we analyze potential forcings for the observed seismicity.

Abstract:Lateral downslope flow in snow during snowmelt and rain-on-snow (ROS) events is a well-known phenomenon, yet its relevance to water redistribution at hillslope and catchment scales is not well understood. We used dye tracers, geophysical methods, and hydrometric measurements to describe the snow properties that promote lateral flow, assess the relative velocities of lateral flow in snow and soil, and estimate volumes of downslope flow. Results demonstrate that rain and melt water can travel tens of metres downslope along layers within the snowpack or at the snowpack base within tens of hours. Lateral flow within the snowpack becomes less likely as the snowpack becomes saturated and stratigraphic boundaries are destroyed. Flow along the base can be prevalent in all snowpack conditions. The net result of lateral flow in snow can be the deposition of water on the soil surface in advanced downslope positions relative to its point of origin, or direct discharge to a stream. Although both melt and ROS events can redistribute water to downslope positions, ROS events produced the most significant volumes of downslope flow. Direct stream contributions through the snowpack during one ROS event produced up to 12% of streamflow during the event. This can help explain rapid delivery of water to streams during ROS events, as well as anomalously high contributions of event water during snowmelt hydrographs. In catchments with a persistent snowpack, lateral redistribution of water within the snowpack should be considered a relevant moisture redistribution mechanism.

Abstract:Many catchment hydrologic and ecologic processes are impacted by the storage capacity of soil water, which is dictated by the profile thickness and water retention properties of soil. Soil water retention properties are primarily controlled by soil texture, which in turn varies spatially in response to microclimate-induced differences in insolation, wetness and temperature. All of these variables can be strongly differentiated by slope aspect. In this study, we compare quantitative measures of soil water retention capacity for two opposing slopes in a semi-arid catchment in southwest Idaho, USA. Undisturbed soil cores from north and south aspects were subjected to a progressive drainage experiment to estimate the soil water retention curve for each sample location. The relatively large sample size (35) supported statistical analysis of slope scale differences in soil water retention between opposing aspects. Soils on the north aspect retain as much as 25% more water at any given soil water pressure than samples from the south aspect slope. Soil porosity, soil organic matter and silt content were all greater on the north aspect, and each contributed to greater soil water retention. These results, along with the observation that soils on north aspect slopes tend to be deeper, indicate that north aspect slopes can store more water from the wet winter months into the dry summer in this region, an observation with potential implications on ecological function and landscape evolution.

Accurately simulating the spatiotemporal distribution of mountain snow water equivalent improves estimates of available meltwater and benefits the water resource management community. In this paper we present the first integration of lidar‐derived distributed snow depth data into a physics‐based snow model using direct insertion. Over four winter seasons (2013–2016) the National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL) Airborne Snow Observatory (ASO) performed near‐weekly lidar surveys throughout the snowmelt season to measure snow depth at high resolution over the Tuolumne River Basin above Hetch Hetchy Reservoir in the Sierra Nevada Mountains of California. The modeling component of the ASO program implements the iSnobal model to estimate snow density for converting measured depths to snow water equivalent and to provide temporally complete snow cover mass and thermal states between flights. Over the four years considered in this study, snow depths from 36 individual lidar flights were directly inserted into the model to provide updates of snow depth and distribution. Considering all updates to the model, the correlation between ASO depths and modeled depths with and without previous updates was on average r2 = 0.899 (root‐mean‐square error = 12.5 cm) and r2 = 0.162 (root‐mean‐square error = 41.5 cm), respectively. The precise definition of the snow depth distribution integrated with the iSnobal model demonstrates how the ASO program represents a new paradigm for the measurement and modeling of mountain snowpacks and reveals the potential benefits for managing water in the region.

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[1] Sliding glaciers and brittle ice failure generate seismic body and surface wave energy characteristic to the source mechanism. Here we analyze continuous seismic recordings from an array of nine short-period passive seismometers located on Bench Glacier, Alaska (USA) (61.033 N, 145.687 W). We focus on the arrival-time and amplitude information of the dominant Rayleigh wave phase. Over a 46-hour period we detect thousands of events using a cross-correlation based event identification method. Travel-time inversion of a subset of events (7% of the total) defines an active crevasse, propagating more than 200 meters in three hours. From the Rayleigh wave amplitudes, we estimate the amount of volumetric opening along the crevasse as well as an average bulk attenuation ( Q = 42) for the ice in this part of the glacier. With the remaining icequake signals we establish a diurnal periodicity in seismicity, indicating that surface run-off and subglacial water pressure changes likely control the triggering of these surface events. Furthermore, we find that these events are too weak (i.e., too noisy) to locate individually. However, stacking individual events increases the signal-to-noise ratio of the waveforms, implying that these periodic sources are effectively stationary during the recording period.