From Substrate to Surface: A Turbulence-based Model to Predict
Interfacial Gas Transfer across Sediment-water-air Interfaces in
Vegetation Streams with Sediments
Abstract
Turbulence generated by aquatic vegetation plays a vital role in the
interfacial transfer process at the air-water interface and
sediment-water interface (AWI and SWI), impacting the dissolved oxygen
(DO) level, a key indicator of water quality for aquatic ecosystems. We
investigated the influence of vegetation, under different submergence
ratios and plant densities, on the interfacial gas transfer mechanisms.
We conducted laboratory experiments in a unidirectional recirculating
flume with simulated rigid vegetation on a sediment bed. Two-dimensional
planar Particle Image Velocimetry (2D-PIV) was used to characterize the
mean flow field and turbulent quantities. Gas transfer rates at the AWI
were determined by monitoring the DO concentration during the
re-aeration process in water. SWI interfacial transfer fluxes were
estimated by measuring the DO concentration difference between the
near-surface and near-bed values. Compared to previous observations on a
smooth bed without sediment, the presence of sediment enhances the
bottom roughness, which generates stronger bed-shear turbulence. The
experimental result shows that turbulence generated from the bed does
not affect the surface transfer process directly. However, the near-bed
suspended sediment provides a negative buoyancy term that reduces the
transfer efficiency according to the predictions by a modified Surface
Renewal model for vegetated flows. The measured interfacial transfer
fluxes across the SWI show a clear dependence on the within-canopy flow
velocity, indicating that bed shear turbulence and within-canopy
turbulence are critical indicators of transfer efficiency at SWI in
vegetated flows. A new Reynolds number dependence model using near-bed
turbulent kinetic energy as an indicator is proposed to provide a
universal prediction for the interfacial flux across the SWI in flows
with aquatic vegetation. Our study provides critical insight for future
studies on water quality management and ecosystem restoration in natural
water environments such as lakes, rivers, and wetlands.