Investigating the Lateral Mixing Coefficient in a Compound Channel with Emergent Vegetation over the Floodplain

Water quality control is very important for people, animals and plants. Predicting the spread of contaminants is important for managing and protecting rivers and streams to the balance of the ecosystem. Pollutants are introduced into waterways, though a variety of sources such as point and non-point sources. Under steady state conditions, where longitudinal mixing is not significant, studying the lateral mixing is essential in evaluating the influence of pollutants on water quality. Lateral or transverse mixing is the hydraulic process by which a plume of contaminant spreads laterally and dilutes. In water quality management, the transverse mixing is more significant than either vertical or longitudinal dispersion, especially, when dealing with the release of wastes from point sources. Hence, a wide range of field, laboratory and numerical modelling approaches, including laboratory and field measurements, and analytical and numerical investigations have been developed, to quantify the lateral mixing coefficient. However, most of the researchers have ignored the effects of vegetation on the lateral mixing process in their studies. Many studies have shown that the flow characteristics through vegetation are different from those in non-vegetated waterways. For example, laboratory studies have revealed that flow velocity and large-scale turbulence tend to be greatly decreased within a plant canopy, because the resistance to flow by the vegetation. Also, vegetation affects the transport of dissolved and particulate material, such as sediment, nutrients and pollutants. In this study, the effect of the floodplain vegetation on lateral mixing coefficient in compound channels is investigated experimentally. Also, a comparison is made between the results of the present study with those obtained by previous researchers.
Experiments were carried out in a laboratory flume 18m long, 0.9m wide and 0.6m high with an asymmetric compound channel section. Three different densities of cylindrical PVC elements of 1 cm diameter were used in addition to the case without cylinders. Three-dimensional flow velocity measurements were taken using a down-looking four beam Acoustic Doppler Velcimeter (ADV). A highly concentrated solution (C0=10 g/L) of red dye (KMnO4, Potassium permanganate) was injected as a tracer sufficiently far downstream of the beginning of the flume such that the flow was fully developed determined by measuring velocity profiles. Variations of tracer concentration at three locations 4.00, 6.44 and 8.88 m downstream of the injection point were determined using image processing technique. In this technique, digital cameras are used at specified cross sections to capture the pixel intensity before and during the passage of the dye cloud. Using the Beer–Lambert Law, the pixel intensity is related to the dye concentration after a simple calibration. Afterward, the images could be used as input files for MATLAB’s Image Processing Toolbox.
The results showed that due to the strong secondary currents and unstable vortexes in the compound channel, the tracer cloud is periodic. The transverse mixing coefficient in the main channel is also always greater than that in the floodplain and its value increases with relative depth. Another factor that was found to affect the lateral mixing coefficient was the vegetation density. The non- dimensioed transverse mixing coefficient increases with vegetation density in the main channel as well as the floodplain. As vegetation density increases from 0.26 to 0.88%, the non- dimensioned transverse mixing coefficient increased up to 40% of the flow relative depth of 0.15. For low density vegetation (0.26%), the lateral mixing coefficient in both the main channel and floodplain was increase upto 30%. Also, for the vegetation density of 0.88%, the lateral mixing coefficient increases up to 80 and 107% for the floodplain and main channel, respectively. As the flow relative depth increase, the effect of the vegetation on the transverse mixing coefficient decreases on both the main channel and floodplain.
It can be concluded that floodplain vegetation affects the transverse mixing coefficient in the main channel and floodplain, significantly. Also, the flow relative depth and vegetation density are two important factors that control the mixing process in compound channels. The results of the present study were in good agreement with those obtained by Lin and Shiono (1995), Siono and Feng (2003), Shiono et al. (2003), Zeng et al. (2008) and Zhang et al. (2010). More researches are needed to extend the findings of the present study to the field applications.