Wind and topography underlie correlation between seasonal snowpack, mountain glaciers, and late-summer streamflow
Year: 2025
Type: article
Abstract: . In a warming climate, net mass loss from perennial snow and ice (PSI) contributes a temporary source of unsustainable streamflow. However, the role of topography and wind in mediating the streamflow patterns of deglaciating watersheds is unknown. We conduct lidar surveys of seasonal snow and PSI elevation change for five adjacent watersheds in the Wind River Range, Wyoming (WRR). Between 2019 and 2023, net mass loss from PSI is equivalent to ~10–36 % of August–September streamflow. Across 338 manually classified PSI features >0.01 km2, glaciers contribute 68 % of the total mass loss, perennial snowfields contribute 8 %, rock glaciers contribute 1 %, buried ice contributes 6 %, and the remaining 17 % derives from semi-annual snowfields and small snow patches. Surprisingly, watersheds with more area-normalized seasonal snow produce less late-summer streamflow (r = -0.60), but this correlation is positive (r = 0.88) considering only deep snow storage (SWE >2 m). Most deep snow (87 %) is associated with favorable topography for wind drift formation. Deep seasonal snow limits the mass loss contribution of PSI features in topographic refugia. We show that watersheds with favorable topography exhibit deeper seasonal snow, more abundant PSI features (and hence greater mass loss during deglaciation), and elevated late-summer streamflow. As a result of deep seasonal snow patterns, watersheds with the most abundant PSI would still produce 45–78 % more late-summer streamflow than nearby watersheds in a counterfactual scenario with zero net mass loss. Similar interrelationships may be applicable to mountain environments globally.
Source: The cryosphere
Authors: Elijah N. Boardman, Andrew G. Fountain, Joseph W. Boardman, Thomas H. Painter, Evan W. Burgess, Laura Wilson, Adrian A. Harpold
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,574
Awards: Collaborative Research: Network Cluster: Using Big Data approaches to assess ecohydrological resilience across scales, G648091085, G7060949742, Collaborative Research Network Cluster: Quantifying controls and feedbacks of dynamic storage on critical zone processes in western montane watersheds
OpenAlex ID: W4413436636
