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Snowdrifts formed by wind transported snow deposition represent a vital component of the earth surface processes on Arctic tundra. Snow accumulation on steep slopes particularly at the margins of rivers, coasts, lakes, and drained lake basins (DLBs) comprise a significant water storage component for the ecosystem during spring and summer snowmelt. The tundra landscape is in constant change as lakes drain, substantially altering the surface morphology that partially controls how snow drifts and accumulates throughout the cold seasons. Here, we combine field measurements, remote sensing observations, and snow modeling to investigate how lake drainage affects snow redistribution at Inigok on the Arctic Coastal Plain of Alaska, where the snow movement is controlled by wind. Field observations included measurements of snow depth using ground penetrating radar and probe. We mapped mid‐July snow cover and modeled snow redistribution before and after drainage simulation for 33 lakes (∼30 km²) in our study area (∼140 km²). Our results show the advantage of using a wide range of snow depth measurements on frozen lakes, DLBs, and upland to validate the snow modeling in order to capture the variability inherent in the landscape. The lake drainage simulation suggests an increase in snow storage of up to ∼24% at DLBs compared to extant lakes, ∼35% considering only snowdrifts (assumed as ≥1 m depth), and ∼4% considering the whole study area. This increase in snow accumulation could significantly impact the landscape when it melts, including wildlife, vegetation, biogeochemical processes, and potential natural hazards like snow‐dam outburst floods.

Warming across the western United States continues to reduce snowpack, lengthen growing seasons, and increase atmospheric demand, leading to uncertainty about moisture availability in montane forests. As many upland forests have thin soils and extensive rooting into weathered bedrock, deep vadose‐zone water may be a critical late‐season water source for vegetation and mitigate forest water stress. A key impediment to understanding the role of the deep vadose zone as a reservoir is quantifying the plant‐available water held there. We quantify the spatiotemporal dynamics of rock moisture held in the deep vadose zone in a montane catchment of the Rocky Mountains. Direct measurements of rock moisture were accompanied by monitoring of precipitation, transpiration, soil moisture, leaf‐water potentials, and groundwater. Using repeat nuclear magnetic resonance and neutron‐probe measurements, we found depletion of rock moisture among all our monitored plots. The magnitude of growing season depletion in rock moisture mirrored above‐ground vegetation density and transpiration, and depleted rock moisture was from ∼0.3 to 5 m below ground surface. Estimates of storage indicated weathered rock stored at least 4%–12% of mean annual precipitation. Persistent transpiration and discrepancies between estimated soil matric potentials and leaf‐water potentials suggest rock moisture may mitigate drought stress. These findings provide some of the first measurements of rock moisture use in the Rocky Mountains and indicated rock moisture use is not just confined to periods of drought or Mediterranean climates.

Time‐lapse electrical resistivity tomography (ERT) data are increasingly used to inform the hydrologic dynamics of mountainous environments at the hillslope scale. Despite their popularity and recent advancements in hydrogeophysical inversion methods, few studies have shown how time‐lapse ERT data can be used to determine hydraulic parameters of subsurface water flow models. This study uses synthetic and field‐collected, hillslope‐scale, time‐lapse ERT data to determine subsurface hydraulic properties of a two‐layer, physics‐based, 2‐D vertical flow model with predefined layer and boundary locations. Uncoupled and coupled hydrogeophysical inversion methods are combined with a fine‐earth fraction optimization scheme to reduce the number of parameters needing calibration and interpret the influence of the hydraulic parameters on the hydrologic model predictions. Inversions of synthetic ERT data recover the prescribed fine‐earth fraction bulk density to within 0.1 g cm⁻³. Field‐collected ERT data from a mountain hillslope result in hydrologic model dynamics that are consistent with previous studies and measured water content data but struggle to capture measured groundwater levels. The uncoupled hydrogeophysical inversion method is more sensitive to changes in hydraulic parameter values of the lower hydrologic model layer than the coupled hydrogeophysical inversion method. Time series of minimum objective function value simulations indicate that periodically collected ERT data may recover hydraulic parameters to a similar level of uncertainty as daily ERT data. Using simple hydrologic model domains within hydrogeophysical inversions shows promise for providing reasonable hydrologic predictions while maintaining relatively simple calibration schemes and should be explored further in future studies.

Lakes and drained lake basins (DLBs) together cover up to ∼80% of the western Arctic Coastal Plain of Alaska. The formation and drainage of lakes in this continuous permafrost region drive spatial and temporal landscape dynamics. Postdrainage processes including vegetation succession and permafrost aggradation have implications for hydrology, carbon cycling, and landscape evolution. Here, we used surface nuclear magnetic resonance (NMR) and transient electromagnetic (TEM) measurements in conjunction with thermal modeling to investigate permafrost aggradation beneath eight DLBs on the western Arctic Coastal Plain of Alaska. We also surveyed two primary surface sites that served as nonlake affected control sites. Approximate timing of lake drainage was estimated based on historical aerial imagery. We interpreted the presence of taliks based on either unfrozen water estimated with surface NMR and/or TEM resistivities in DLBs compared to measurements on primary surface sites and borehole resistivity logs. Our results show evidence of taliks below several DLBs that drained before and after 1949 (oldest imagery). We observed depths to the top of taliks between 9 and 45 m. Thermal modeling and geophysical observations agree about the presence and extent of taliks at sites that drained after 1949. Lake drainage events will likely become more frequent in the future due to climate change and our modeling results suggest that warmer and wetter conditions will limit permafrost aggradation in DLBs. Our observations provide useful information to predict future evolution of permafrost in DLBs and its implications for the water and carbon cycles in the Arctic.