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River Dynamics Control Transit Time Distributions and Biogeochemical Reactions in a Dam‐Regulated River Corridor
Author(s) -
Song Xuehang,
Chen Xingyuan,
Zachara John M.,
GomezVelez Jesus D.,
Shuai Pin,
Ren Huiying,
Hammond Glenn E.
Publication year - 2020
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2019wr026470
Subject(s) - biogeochemical cycle , environmental science , advection , hydrology (agriculture) , geology , geotechnical engineering , chemistry , physics , environmental chemistry , thermodynamics
Transit time distributions (TTDs) exert important controls on biogeochemical processes in watershed systems. TTDs are often assumed to follow time‐invariant exponential, lognormal, or heavy‐tailed power law distributions in headwater or low‐order streams. However, under dynamic hydrological forcing, transit time could exhibit more complex distribution patterns with strong spatial and temporal variability. In this study, we used a numerical particle tracking approach to characterize TTDs along the Hanford Reach of the Columbia River under the influences of river stage fluctuations and evaluate the associated effects on biogeochemical reaction potentials within the river corridor. Particle tracking was conducted using velocity fields simulated by high‐resolution three‐dimensional groundwater flow models that capture both the river stage fluctuations and physical heterogeneity. Our results revealed that multifrequency flow variations led to multimodal TTDs that varied in time and space. Such characteristics can only be captured by multiyear numerical simulations supported by multiyear field monitoring. Dam‐induced high‐frequency (subweekly) flow variations increased additional hydrologic exchange flows with short (subweekly) transit times, which accounted for up to 44% of reactant consumption in the river corridor along the Hanford Reach. The dam‐induced river stage fluctuations have more significant impacts on faster biogeochemical reactions because they cause a larger fraction of shorter transit times. Numerical particle tracking provides an efficient alternative for characterizing TTDs for large complex systems where in situ field experiments are not feasible. Such a numerical approach is thus essential for improving large‐scale biogeochemical modeling from watersheds to basins.