TY - JOUR
T1 - Constraining Bedrock Groundwater Residence Times in a Mountain System With Environmental Tracer Observations and Bayesian Uncertainty Quantification
AU - Thiros, Nicholas E.
AU - Siirila-Woodburn, Erica R.
AU - Dennedy-Frank, P. James
AU - Williams, Kenneth H.
AU - Gardner, W. Payton
N1 - Publisher Copyright:
© 2023. The Authors.
PY - 2023/2
Y1 - 2023/2
N2 - Groundwater residence time distributions provide fundamental insights on the hydrological processes within watersheds. Yet, observations that can constrain groundwater residence times over broad timescales remain scarce in mountain catchment studies. We use environmental tracers (CFC-12, SF6, 3H, and 4He) to investigate groundwater residence times along a hillslope in the East River Watershed, Colorado, USA. We develop a Bayesian inference framework that applies a Markov-chain Monte Carlo (MCMC) approach to estimate noble gas recharge temperature, elevation, and excess-air parameters and the resulting environmental tracer concentrations. MCMC is then used to propagate the environmental tracer uncertainties to estimates of groundwater mean residence times inferred with lumped parameter models. All samples contain 3H, CFC-12, and SF6 in addition to terrigenic 4He, suggesting a mixture of water characterized by modern and premodern residence times. 4He exponential mean residence times range from hundreds of years at the upslope well to thousands of years at the toe-slope well assuming average crustal production rates. We find that binary mixing residence time distributions with separate young and old mixing fractions are needed to predict the 4He, CFC-12, SF6, and 3H observations, supporting the importance of flow path mixing in this bedrock system. Our findings that the fractured bedrock hosts groundwater with a mixture of residence times ranging from decades to millennia suggest variable recharge dynamics and flow path mixing along the hillslope and highlight the importance of characterizing groundwater systems with observations that are sensitive to transport over a broad range of residence times.
AB - Groundwater residence time distributions provide fundamental insights on the hydrological processes within watersheds. Yet, observations that can constrain groundwater residence times over broad timescales remain scarce in mountain catchment studies. We use environmental tracers (CFC-12, SF6, 3H, and 4He) to investigate groundwater residence times along a hillslope in the East River Watershed, Colorado, USA. We develop a Bayesian inference framework that applies a Markov-chain Monte Carlo (MCMC) approach to estimate noble gas recharge temperature, elevation, and excess-air parameters and the resulting environmental tracer concentrations. MCMC is then used to propagate the environmental tracer uncertainties to estimates of groundwater mean residence times inferred with lumped parameter models. All samples contain 3H, CFC-12, and SF6 in addition to terrigenic 4He, suggesting a mixture of water characterized by modern and premodern residence times. 4He exponential mean residence times range from hundreds of years at the upslope well to thousands of years at the toe-slope well assuming average crustal production rates. We find that binary mixing residence time distributions with separate young and old mixing fractions are needed to predict the 4He, CFC-12, SF6, and 3H observations, supporting the importance of flow path mixing in this bedrock system. Our findings that the fractured bedrock hosts groundwater with a mixture of residence times ranging from decades to millennia suggest variable recharge dynamics and flow path mixing along the hillslope and highlight the importance of characterizing groundwater systems with observations that are sensitive to transport over a broad range of residence times.
KW - catchment hydrology
KW - dissolved noble gases
KW - environmental tracers
KW - groundwater residence times
KW - uncertainty analysis
UR - http://www.scopus.com/inward/record.url?scp=85148706056&partnerID=8YFLogxK
U2 - 10.1029/2022WR033282
DO - 10.1029/2022WR033282
M3 - Article
AN - SCOPUS:85148706056
SN - 0043-1397
VL - 59
JO - Water Resources Research
JF - Water Resources Research
IS - 2
M1 - e2022WR033282
ER -