Physically Based Scaling Models to Predict Gas Transfer Velocity in Streams and Rivers
Junna Wang, Fabián A. Bombardelli, Xiaoli Dong
Abstract
Abstract Air‐water gas transfer influences fundamental processes of aquatic systems such as photosynthesis, respiration, and greenhouse gas emission. Previous predictive models for gas transfer velocity ( K L ) often only apply to a small range of streams and rivers. Two “universal” scalings, K L ∼ 1/4 power of turbulent dissipation rate ( ε 1/4 ) and K L ∼ shear velocity ( U *), deduced from classic thin‐film theory and surface renewal theory, have been reported for lake and marine systems, but have not been adequately tested for streams or rivers. To test the two scalings and understand how K L varies across systems, we compiled 588 field measurements of K L , and used inverse modeling based on long‐term high‐frequency dissolved oxygen time series to estimate K L of 35 streams and rivers capturing a wide range of discharge (0–221 m 3 /s). We found that the two scalings held for both the K L estimated by inverse modeling and the K L from measurements and outperformed 23 previous models in predicting K L . Furthermore, the main driver of K L variation shifts from bottom friction to other factors with increasing stream/river size. In most streams and a few rivers, correlation between U * and K L is high, and discharge‐ K L relationships are strongly positive, indicating that turbulence generated by bottom friction dominates near‐surface turbulence, a fundamental control of K L , thus, the two scaling models are applicable to these systems. However, most rivers (mean discharge >10 m 3 /s) show low correlations between U * and K L , suggesting biochemical factors and winds likely override bottom friction in driving near‐surface turbulence and K L .