Predicting the buffering of acid plumes within estuaries

The acid buffering capacity of an estuary is directly proportional to the volume of buffering agents within the system. In areas with limited upstream inflows of buffering agents, the primary buffering agents are sourced from the diffusion of marine constituents. During dry periods the buffering capacity increases with tidal diffusion, whereas buffering decreases following estuarine flushing from high inflows. In acid sulphate soil environments, acidic discharges are generated immediately following rainfall events. Thereby, the diffusion of buffering agents throughout an estuary plays an important role in sustaining biogeochemical processes. Prediction of the transport and buffering dynamics of acidic plumes within estuaries allows severely impacted acid areas to be identified and catchment management strategies developed.To simulate acid transport and tidal buffering processes within an estuary, a numerical model was modified and an acidic buffering module included within the hydrodynamic routine. An estuarine wide case study was then undertaken to demonstrate the effectiveness of the acid plume module in simulating onsite conditions and the role of buffering versus dilution. Acid discharged from the study domain, located on a tidal barrier estuary in south-eastern Australia, was monitored using fixed and boat mounted instrumentation to track far-field plume behaviour. The acidic plume monitoring results were converted to hydrogen proton concentrations and included within the water quality module to simulate acid buffering with bicarbonate ions diffusing from the marine boundary.The validated model can be applied to single or multi-drain estuary networks to assess possible management options for reducing the impact of acid plume events. This enables the most effective management approach to be identified and assists in prioritising acid sulphate soil sites for remediation. This is particularly useful to natural resource managers in order to assess remediation sites that have the most environmental impact, or can be most effectively buffered, via model scenario tests.