Quantifying turbulent mixing and oxygen fluxes in a Mediterranean-type, microtidal estuary

Experiments were carried out on an intermittent estuary during its closed (summer) and open (winter) states to identify the physical processes responsible for vertical mixing across the halocline, and to quantify vertical fluxes of oxygen and salt between water layers. During the blocked phase a two-layer structure was observed, with a brackish surface layer overlying old seawater. Within a deep basin the wind-driven turbulent mixing was consistent with the measured surface-layer turbulent dissipation, but the dissipation in the bottom layer appeared to be driven by internal seiching. In the shallow regions of the estuary vertical fluxes of dissolved oxygen were indicative of oxygen demand by respiration and remineralization of organic material in bottom water and sediments. During the estuary's open phase a three-layer structure was observed, having a fresh, river-derived surface layer, a middle layer of new seawater, and a bottom layer of old seawater. In the shallower regions surface-layer turbulent diffusion was consistent with the strong, gusty winds experienced at the time. The dissolved oxygen of the incoming seawater decreased to very low values by the time it reached the upstream deep basin as a result of the low cross-pycnocline oxygen flux being unable to compensate for the oxygen utilization. At least 50 % of the cross-pycnocline salt fluxes in the shallow reaches of the open estuary are suggested to be driven by Holmboe instabilities.

Modelling blackwater: predicting water quality during flooding of lowland river forests

The blackwater model was developed to predict adverse water quality associated with flooding of the Barmah-Millewa Forests on the River Murray. Specifically, the model examines the likelihood and severity of blackwater events—high dissolved organic carbon associated with low dissolved oxygen. The Barmah-Millewa Forests are dominated by an overstorey of River Red Gum (Eucalyptus camaldulensis) and the litter from these trees contributes a substantial proportion of the pulse of dissolved organic matter released from the floodplain during flooding. This model examines rates of litter accumulation and decay on the floodplain (prior to and during flooding), rates of carbon leaching, microbial degradation, oxygen consumption, reaeration processes and the effects of flow on the concentrations of dissolved organic carbon and dissolved oxygen in the water column (both on the floodplain and in the river channel downstream). The model has been calibrated with data from two blackwater events that have taken place in these forests within the last 5 years. Scenario testing with the model highlights the particularly important roles of flow and temperature in the development of anoxia. Pooled floods and those in the warmest months of the year are substantially more likely to result in blackwater events than floods in cooler times of the year and involving more water exchange between the river channel and the floodplain.

Demo abstract: wind measurements for water quality studies in urban reservoirs

Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.