Eight WRL students complete PhDs in six-month period

Danial’s PhD presents a systematic hydrodynamic understanding of different estuaries and tidal rivers in present-day and future conditions to detail the influence of sea-level rise (SLR) on tidal dynamics, establish a framework for assessing SLR effects on estuaries worldwide, and guide decision-makers in establishing holistic, evidence-based management plans for these valuable environments. The numerical approach and learnings presented in his PhD thesis could be used to identify estuaries that are most vulnerable to SLR-induced tidal variations (e.g., changes in high tide flooding, drainage efficiency, sediment transport, tidal energy) and to predict cumulative SLR impacts on estuaries at a global scale. 

Sandy beaches play a compelling role in our society, providing economic development and allowing for human settlement.  In a changing climate, expected future modifications in waves and storm activity, together with sea level rise, can lead to increased coastal erosion and flooding, threatening the fate of sandy beaches. To improve our predictive capabilities of sandy shoreline evolution to these changes in climate forcing, Raimundo’s researched focused on revealing how sandy beaches naturally evolve and adjust from seasonal to interannual (several years to decades) time scales. Through data analyses (machine learning, clustering), data assimilation and numerical modelling approaches, his research provided new insights on the physical drivers of shoreline change from single beaches to regional scales, as well as new ways to improve future shoreline change predictions in a changing climate.

Sandy beach and dune systems often provide coastal communities with the first line of defence from the impacts of extreme storm events. However, predicting both the nature and severity of these hazards is challenging, especially at the regional-scale (100-1000s kms). Christopher’s thesis first introduced a new conceptual framework for classifying storm hazards, before a simple decision tree approach to forecasting beach erosion was explored. Finally, recent advances in machine learning were leveraged and a gradient boosted random forest ensemble was trained to provide probabilistic forecasts of beach erosion impacts. It is anticipated the findings of this thesis can inform the implementation of future coastal storm impact EWSs around the world.

40% of the world's populations live within 100 kilometres of the coast. Consequently, these coastal areas are typically highly urbanised and therefore more vulnerable to the impacts of hazards such as extreme coastal storms. During his PhD, Nash developed a framework for a coastal hazard early warning system that can provide timely and effective information on potential erosion that can occur along coastlines, several days ahead of the storm event. When implemented, this system will predict with a certain degree of certainty, the location and magnitude of the expected erosion so that emergency response teams can take action to reduce the risk to those that are exposed to the hazard.

Small, constructed waterbodies are designed to attenuate floods and enhance water quality. Despite a range of guidelines that inform the design of these waterbodies, many still experience harmful algal blooms (HABs). It is vital to improve our understanding of how small waterbodies respond to HABs, considering the increasing number of small waterbodies being built globally and increasing HAB risk with climate change. This thesis provided design recommendations for small, constructed waterbodies to limit HABs, and tested the utility of remote sensing detection methods for HABs and water quality in these waterbodies.

Eutrophication is caused by high concentrations of nutrients, namely phosphorus and nitrogen, entering waterways.  Wastewater pollution contributes to these nutrient loads and accounts for approximately 15% of all river inflows worldwide.  Impacts can range from the restricted use of local waterways in-line with community values, including fishing and swimming, to outbreaks of algal blooms that inhibit aquatic productivity (e.g., fish kills), and human health issues associated with pathogens.  Jamie’s PhD integrated best practice numerical modelling methods and microbial science to determine the role of microbes in responding to, and processing nutrients from, treated effluent.  The outcomes will assist with (i) developing monitoring programs that better our understanding of waterway functioning, (ii) accurately representing biophysical processes throughout an entire waterway, and (iii) developing integrated catchment management plans. 

Sandy coastlines are dynamic landscapes that constantly evolve as they respond to environmental conditions like waves, coastal storms, and tides. Along many urbanised coastlines, these changes can have disastrous consequences on beachfront infrastructure and property. A better understanding of how shorelines advance and retreat is the key to a successful management of our coastlines. Kilian’s  PhD research provides new tools to monitor coastlines from space, leveraging the 35-year archive of publicly available satellite imagery. These tools were all made open-source and can be used by coastal managers and engineers worldwide to gain insights into coastal change patterns and trends at their local beach. In my thesis, these novel tools are used to investigate the impact of El Nino Southern Oscillation on beach changes across the Pacific, highlighting the vulnerability of the East coast of Australia during La Nina phases.