Search for: All records

Climate warming in alpine regions is changing patterns of water storage, a primary control on alpine plant ecology, biogeochemistry, and water supplies to lower elevations. There is an outstanding need to determine how the interacting drivers of precipitation and the critical zone (CZ) dictate the spatial pattern and time evolution of soil water storage. In this study, we developed an analytical framework that combines intensive hydrologic measurements and extensive remotely-sensed observations with statistical modeling to identify areas with similar temporal trends in soil water storage within, and predict their relationships across, a 0.26 km 2 alpine catchment in the Colorado Rocky Mountains, U.S.A. Repeat measurements of soil moisture were used to drive an unsupervised clustering algorithm, which identified six unique groups of locations ranging from predominantly dry to persistently very wet within the catchment. We then explored relationships between these hydrologic groups and multiple CZ-related indices, including snow depth, plant productivity, macro- (10 2 ->10 3 m) and microtopography (<10 0 -10 2 m), and hydrological flow paths. Finally, we used a supervised machine learning random forest algorithm to map each of the six hydrologic groups across the catchment based on distributed CZ properties and evaluated their aggregate relationships at the catchment scale. Our analysis indicated that ~40–50% of the catchment is hydrologically connected to the stream channel, lending insight into the portions of the catchment that likely dominate stream water and solute fluxes. This research expands our understanding of patch-to-catchment-scale physical controls on hydrologic and biogeochemical processes, as well as their relationships across space and time, which will inform predictive models aimed at determining future changes to alpine ecosystems. 

The glaciers of the Cordillera Blanca, Peru, are rapidly retreating and thinning as a result of climate change, altering the timing, quantity and quality of water available to downstream users. Furthermore, increases in the number and size of proglacial lakes associated with these melting glaciers is increasing potential exposure to glacier lake outburst floods (GLOFs). Understanding how these glaciers are changing and their connection to proglacial lake systems is thus of critical importance. Most satellite data are too coarse for studying small mountain glaciers and are often affected by cloud cover, while traditional airborne photogrammetry and lidar are costly. Recent developments have made unmanned aerial vehicles (UAVs) a viable and potentially transformative method for studying glacier change at high spatial resolution, on demand and at relatively low cost.

Using a custom designed hexacopter built for high-altitude (4000–6000 m a. s. l. ) operation, we completed repeat aerial surveys (2014 and 2015) of the debris-covered Llaca Glacier tongue and proglacial lake system. High-resolution orthomosaics (5 cm) and digital elevation models (DEMs) (10 cm) were produced and their accuracy assessed. Analysis of these datasets reveals highly heterogeneous patterns of glacier change. The most rapid areas of ice loss were associated with exposed ice cliffs and meltwater ponds on the glacier surface. Considerable subsidence and low surface velocities were also measured on the sediments within the pro-glacial lake, indicating the presence of extensive regions of buried ice and continued connection to the glacier tongue. Only limited horizontal retreat of the glacier tongue was observed, indicating that measurements of changes in aerial extent alone are inadequate for monitoring changes in glacier ice quantity. 

The seasonal snowmelt period is a critical component of the hydrologic cycle for many mountainous areas. Changes in the timing and rate of snowmelt as a result of physical hydrologic flow paths, such as longitudinal intra‐snowpack flow paths, can have strong implications on the partitioning of meltwater amongst streamflow, groundwater recharge, and soil moisture storage. However, intra‐snowpack flow paths are highly spatially and temporally variable and thus difficult to observe. This study utilizes new methods to non‐destructively observe spatio‐temporal changes in the liquid water content of snow in combination with plot experiments to address the research question: What is the scale of influence that intra‐snowpack flow paths have on the downslope movement of liquid water during snowmelt across an elevational gradient? This research took place in northern Colorado with study plots spanning from the rain‐snow transition zone up to the high alpine. Results indicate an increasing scale of influence from intra‐snowpack flow paths with elevation, showing higher hillslope connectivity producing larger intra‐snowpack contributing areas for meltwater accumulation, quantified as the upslope contributing area required to produce observed changes in liquid water content from melt rate estimates. The total effective intra‐snowpack contributing area of accumulating liquid water was found to be 17, 6, and 0 m²for the above tree line, near tree line, and below tree line plots, respectively. Dye tracer experiments show capillary and permeability barriers result in increased number and thickness of intra‐snowpack flow paths at higher elevations. We additionally utilized aerial photogrammetry in combination with ground penetrating radar surveys to investigate the role of this hydrologic process at the small watershed scale. Results here indicate that intra‐snowpack flow paths have influence beyond the plot scale, impacting the storage and transmission of liquid water within the snowpack at the small watershed scale.