Why Are Some Rocky Mountain Lakes Ephemeral?

Abstract

Small mountain lakes function as temporary storage basins for rain and snowmelt‐derived water. Many small lakes lose water seasonally, but questions remain about the processes involved and effects on watershed hydrology. Evaporation and groundwater outflow from lakes may influence baseflow in streams, hydrologic connections among lakes, and water fluxes from a watershed. To evaluate the role of small mountain lakes in watershed hydrology and the dominant pathways of water loss, we studied the water balances of four shallow, closed‐basin, subalpine lakes in southern Wyoming that lose up to 99% of their volumes between early summer and late fall. We tested the performance of seven evaporation models, compared observed rates of water loss with simulations of evaporation and drainage, and conducted geophysical surveys to evaluate the hydrologic environment between lakes. Our results show that groundwater outflow, rather than evaporation, can dominate water loss and cause closed‐basin mountain lakes to be ephemeral. Groundwater fluxes may contribute to varied rates and timing of water loss from the lakes. Evaporation accounted for 14% of water loss in a lake that overlays thin (<0.5 m) sediments and fractured bedrock and 83% in a lake underlain by >3 m of sediments and clay. Gradual recharge of groundwater (<18,000 m3·km−2·day−1) from each study lake likely helps sustain baseflow in streams once snowmelt has subsided. Total water loss from closed‐basin, subalpine lakes may therefore help to maintain baseflow of rivers in late summer, but their impact varies based on geological context and snowmelt availability.

Millennial-scale increase in winter precipitation in the southern Rocky Mountains during the Common Era

“…8B). The timing of these highest Holocene lake levels are contemporaneous with the switch to positive winter precipitation anomalies, which fits with the expectation that small lakes depend primarily on spring snowpack for maintaining high water levels even in late summer and fall (Shuman et al, 2009; Liefert et al, 2018). Consequently, the late Holocene highstands likely reflect a high winter precipitation regime starting between ca.…”

Global Isotope Hydrogeology―Review

“…Incorporating spatial variability of precipitation isotope compositions into hydrogeological models may improve interpretations of groundwater isotope compositions (e.g., the range of elevations at which the mixture of groundwaters in the sample recharged). What remains unclear is the relative relevance of diffuse versus focused groundwater recharge for high‐elevation recharge, and how the importance of each mechanism varies spatially (e.g., importance of focused recharge from mountain lakes demonstrated by Liefert et al, ).…”

“…Assessing annual recharge rates is important for estimating the extent to which groundwater pumping impacts groundwater storage and discharge (Theis, , ). Yet understanding recharge rates at shorter (i.e., seasonal) timescales is also important in order to (i) forecast changes to annual recharge rates under changing seasonal climate conditions (e.g., Ajami et al, ; Earman et al, ; Earman & Dettinger, ; Meixner et al, ; Niraula et al, ), (ii) develop more sophisticated conceptual models detailing hydrological processes and conditions conducive to groundwater replenishment (e.g., Alsaaran, ; Dripps, ; Dripps & Bradbury, ; Flerchinger et al, ; Gat & Tzur, ; Gates, Edmunds, Ma, et al, ; Hammarlund & Edwards, ; Liefert et al, ; Nasta et al, ; Pavlovskii et al, ; Rathay et al, ; Wilson & Guan, ; Zhang et al, ), (iii) interpret paleoclimate conditions from fossil groundwater and speleothem isotopic records (e.g., Bar‐Matthews et al, ; Benson & Klieforth, ; Denniston et al, ; Fairchild et al, ; Johnson, Hu, et al, ; Johnson, Ingram, et al, ; Jones et al, ; Simpson et al, ; Treble et al, ), and (iv) understand the ways that plants obtain water, and the relationships among vegetation, runoff, and recharge (e.g., Grossiord et al, ; Guswa & Spence, ; Kim & Jackson, ; Vico et al, ).…”

Research on Digital Economy and Human Resources Based on Fuzzy Clustering and Edge Computing

“…For example, scholars John Helitanker and Ron S. Jarmon constructed only an evaluation index system for the development of the digital economy. e paper proposes a method to measure the digital economy, and the existing quantitative research is mostly limited to the use of simple, descriptive, and statistical analysis for quantitative analysis, lacks objective, comprehensive, and systematic quantitative research results, and cannot accurately reflect the current situation of my country's digital economy development in a timely manner [14,15]. erefore, based on the combination of the existing research results of the same kind at home and abroad, this article firstly defines the connotation of the digital economy and its development characteristics and builds a digital economy development evaluation index system on this basis and then conducts a review of the development status of China's digital economy.…”