Turbulence and mixing in a freshwater-influenced tidal bay: Observations and numerical modeling

In situ observations and numerical simulations of turbulence are essential to understanding vertical mixing processes and their dynamical controls on both physical and biogeochemical processes in coastal embayments. Using in situ data collected by bottom-mounted acoustic Doppler current profilers(ADCPs) and a free-falling microstructure profiler, as well as numerical simulations with a second-moment turbulence closure model, we studied turbulence and mixing in the Xiamen Bay, a freshwater-influenced tidal bay located at the west coast of the Taiwan Strait. Dynamically, the bay is driven predominantly by the M2 tide, and it is under a significant influence of the freshwater discharged from the Jiulong River. It is found that turbulence quantities such as the production and dissipation rates of the turbulent kinetic energy(TKE) were all subject to significant tidal variations, with a pronounced ebb-flood asymmetry. Turbulence was stronger during flood than ebb. During the flooding period, the whole water column was nearly well mixed with the depth-averaged TKE production rate and vertical eddy viscosity being up to 5?10?6 W kg?1 and 2?10?2 m2 s?1, respectively. In contrast, during the ebb strong turbulence was confined only to a 5?8 m thick bottom boundary layer, where turbulence intensity generally decreases with distance from the seafloor. Diagnosis of the potential energy anomaly showed that the ebb-flood asymmetry in turbulent dissipation and mixing was due mainly to tidal straining process as a result of the interaction between vertically shared tidal currents and horizontal density gradients. The role of vertical mixing in generating the asymmetry was secondary. A direct comparison of the modeled and observed turbulence quantities confirmed the applicability of the second-moment turbulence closure scheme in modeling turbulent processes in this weakly stratified tidally energetic environment, but also pointed out the necessity of further refinements of the model.

A combined numerical tidal model for the Hangzhou Bay and Qiantang River

-In order to avoid prescribing open boundary condition on the upstream side of the Hangzhou Bay, in numerical simulation of the tides and residual currents of the Bay, a 1-D model for the Qiantang River is connected to the 2-D model for the Hangzhou Bay. The harmonic constants of diurnal constituent [ (K1+O1)/2],semidiurnal constituent (M2) and shallow water constituent (M4) are obtained. The results produced by the combined model are in better agreement with the observed ones than those produced solely by the original 2-D model. The combined model gives much more reliable results for tide-induced residual water level and current.

Seasonal dynamics of meiofaunal distribution in the Dagu River Estuary, Jiaozhou Bay, China

Sediment samples were collected in the intertidal zone of the Dagu River Estuary, Jiaozhou Bay, China in April,July and October 2010 and February 2011 for examining seasonal dynamics of meiofaunal distribution and their relationship with environmental variables. A total of ten meiofaunal taxa were identified, including free-living marine nematodes, benthic copepods, polychaetes, oligochaetes, bivalves, ostracods, cnidarians, turbellarians,tardigrades and other animals. Free-living marine nematodes were the most dominant group in both abundance and biomass. The abundances of marine nematodes were higher in winter and spring than those in summer and autumn. Most of the meiofauna distributed in the 0–2 cm sediment layer. The abundance of meiofauna in hightidal zone was lower than those in low-tidal and mid-tidal zones. Results of correlation analysis showed that Chlorophyll a was the most important factor to influence the seasonal dynamics of the abundance, biomass of meiofauna and abundances of nematodes and copepods. CLUSTER analysis divided the meiofaunal assemblages into three groups and BIOENV results indicated that salinity, concentration of organic matter, sediment sorting coefficient and sediment median diameter were the main environmental factors influencing the meiofaunal assemblages.