2021
DOI: 10.1002/hyp.14029
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Seasonal connections between meteoric water and streamflow generation along a mountain headwater stream

Abstract: In snowmelt-driven mountain watersheds, the hydrologic connectivity between meteoric waters and stream flow generation varies strongly with the season, reflecting variable connection to soil and groundwater storage within the watershed. This variable connectivity regulates how streamflow generation mechanisms transform the seasonal and elevational variation in oxygen and hydrogen isotopic composition (δ 18 O and δD) of meteoric precipitation. Thus, water isotopes in stream flow can signal immediate connectivit… Show more

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Cited by 7 publications
(6 citation statements)
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References 80 publications
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“…These uncertainties can be reduced in future research by obtaining sublimation estimates from eddy‐covariance towers and employing more sophisticated simulations of the catchment's hydrological cycle that offer a more accurate representation of soil characteristics and groundwater processes. In addition, despite the considerable number of water samples taken in this study, the application of hydrograph separation based on water isotopes is complicated by the lack of detailed control of isotopic variations in individual precipitation events, water stored in soils and groundwater, and distributed samples of snowpack isotopy (Kamensky, 1998; Lee et al, 2010; Leuthold et al, 2021; Schmieder et al, 2016). Such monitoring should also be considered in further research.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…These uncertainties can be reduced in future research by obtaining sublimation estimates from eddy‐covariance towers and employing more sophisticated simulations of the catchment's hydrological cycle that offer a more accurate representation of soil characteristics and groundwater processes. In addition, despite the considerable number of water samples taken in this study, the application of hydrograph separation based on water isotopes is complicated by the lack of detailed control of isotopic variations in individual precipitation events, water stored in soils and groundwater, and distributed samples of snowpack isotopy (Kamensky, 1998; Lee et al, 2010; Leuthold et al, 2021; Schmieder et al, 2016). Such monitoring should also be considered in further research.…”
Section: Discussionmentioning
confidence: 99%
“…During the melting season, rain provides a large streamflow contribution, and the meltwater contribution is often difficult to infer. Stable water isotopes (generally δ 2 H and δ 18 O) have helped to better understand the contribution of snowmelt to streamflow and the residence time of melting water in the catchments (Leuthold et al, 2021; McGill et al, 2021; Penna et al, 2017), thanks to the more depleted isotopic values of the melted snow compared to streamflow (McGill et al, 2021; Vystavna et al, 2021). However, a full separation of the contribution of each component is difficult to obtain, since it requires a very intense spatially and temporally isotopic sampling of each component.…”
Section: Introductionmentioning
confidence: 99%
“…The mean isotopic values of the recorded series show strong interannual differences, exhibiting higher (lower) values during the snow poor (rich) seasons. However, the application of hydrograph separation based on water isotopes is complicated by the lack of detailed control of isotopic variations in individual precipitation events, water stored in soils and groundwater, and distributed samples of snowpack isotopy (Kamensky, 1998;Lee et al, 2010;Leuthold et al, 2021;Schmieder et al, 2016). Such monitoring should be considered in further research.…”
Section: Discussionmentioning
confidence: 99%
“…During the melting season, rain provides a large streamflow contribution, and the meltwater contribution is often difficult to infer. Stable water isotopes (generally δ 2 H and δ 18 O) have resulted extremely useful to better understand the contribution of snowmelt to streamflow and the residence time of melting water in the catchments (Leuthold et al, 2021;McGill et al, 2021;Penna et al, 2017), thanks to the more depleted values of snow isotopy compared to streamflow (McGill et al, 2021;Vystavna et al, 2021). However, a full separation of the contribution of each component is difficult to obtain, since it requires a very intense spatially and temporally isotopic sampling of each component.…”
Section: Introductionmentioning
confidence: 99%
“…To allow assessment of meaningful deviation of environmental waters from the LMWL, the analytical uncertainty estimates of 0.6‰ for δ 18 O and 0.9‰ for δ 2 H were used in a Monte Carlo propagation of uncertainty to the LMWL, following the approach of Leuthold et al (2021). The Monte Carlo ensemble consisted of 5000 realizations to propagate analytical uncertainty to the slope and intercept of the LMWL calculated from precipitation sample results.…”
Section: Methodsmentioning
confidence: 99%