Quantifying seasonal volume of groundwater in high elevation meadows: Implications for complex aquifer geometry in a changing climate

The hydrologic impacts of rising global temperatures are severe and imminent particularly in snow-dominated regions. In the western United States, high elevation meadows are among the ecosystems highly sensitive to climate change. High elevation meadows are groundwater dependent ecosystems and rely on seasonal snowpack melt in order to support ecologic function and baseflow to streams. This stream flow in turn supplies an estimated 2.6 million San Francisco residents with water. Once the snow melts and recharges the aquifer, groundwater supports vegetation separate from the surrounding hillslopes, which promotes important ecologic functions like flood regulation and nutrient cycling. Groundwater also supports baseflow to perennial rivers late into the summer months transferring this snowmelt to downstream ecologic and human communities. By 2100 snowpack accumulation in the Sierra Nevada is expected to decrease by ~40-90% due to near-surface temperature rise. Though precipitation intensity is not expected to change, a decrease in snowpack will change the timing and magnitude of groundwater recharge necessary to sustain high elevation meadows. An additional climate-driven shift and decrease in peak stream flow to early spring away from summer when demand is highest puts into question ecosystem survivability and water supply to downstream users. Here, a new quantitative framework is presented to lay the foundation for the widespread identification of vulnerabilities in high elevation meadows due to climate change. This research proposed and tested a new conceptual model for the volume of groundwater stored in high elevation meadows similar to that of a reservoir with active and dead storage. The seasonal fluctuations in active storage, which is defined as the volume of groundwater able to exchange between the aquifer, streams, and vegetation, are thought to be highly sensitive to aquifer parameters, such as bedrock geometry, meadow gradient, and hydraulic conductivity. In order to test this hypothesis, this research first identified complex aquifer geometry controlled by bedrock depths from a ground-penetrating radar field campaign in Tuolumne Meadows, CA. This research then quantified the hydrogeologic impacts of a uniform sediment thickness model against a variable sediment thickness model under scenarios that simulated different high elevation meadows by incorporating ranges of hydraulic conductivity and topographic gradient. These scenarios also tested different stream flow and recharge rates, which simulated different volumes of snowpack. Results imply that bedrock geometry impact both the timing and magnitude of volume of groundwater (i.e. active storage) retention as well as release to streams and vegetation under both current and future snowpack simulations. In most cases, a uniform thickness meadow overestimated volume of groundwater retained from recharge and released to the stream both spatially and temporally. In doing so, volume of surface water transferred to downstream users was also overestimated. These overestimations are significant and, depending on the type of meadow, can miscalculate the water supply to San Francisco by several days worth of water. This research also indicated a reduction of up to 70% water supply from these meadows as a result of future decreases in snowpack. Spatially within the meadow, a uniform thickness model further overestimated volume of groundwater nearest to bedrock outcrops. This suggested that a uniform thickness model did not successfully identify spatially vulnerable regions on the meadow scale. This research concludes that efficient and effective monitoring and management of the water to and from these ecosystems must consider the substantial impacts of complex aquifer geometry.