Dr Michael Kinsela

The potential response of shoreface depositional environments to sea level rise over the present century and beyond remains poorly understood. The shoreface is shaped by wave action across a sedimentary seabed and may aggrade or deflate depending on the balance between time-averaged wave energy and the availability and character of sediment, within the context of the inherited geological control. For embayed and accommodation-dominated coastal settings, where shoreline change is particularly sensitive to cross-shore sediment transport, whether the shoreface is a source or sink for coastal sediment during rising sea level may be a crucial determinant of future shoreline change. While simple equilibrium-based models (e.g. the Bruun Rule) are widely used in coastal risk planning practice to predict shoreline change due to sea level rise, the relevance of fundamental model assumptions to the shoreface depositional setting is often overlooked due to limited knowledge about the geomorphology of the nearshore seabed. We present high-resolution mapping of the shoreface-inner shelf in southeastern Australia from airborne lidar and vessel-based multibeam echosounder surveys, which reveals a more complex seabed than was previously known. The mapping data are used to interpret the extent, depositional character and morphodynamic state of the shoreface, by comparing the observed geomorphology to theoretical predictions from wave-driven sediment transport theory. The benefits of high-resolution seabed mapping for improving shoreline change predictions in practice are explored by comparing idealised shoreline change modelling based on our understanding of shoreface geomorphology and morphodynamics before and after the mapping exercise.

CoastSnap is a low-cost community beach monitoring program that turns everyday smartphones into devices to measure coastal response to storms, sea-level rise, human modifications and other factors. Underpinning CoastSnap is a stainless-steel smartphone cradle that is installed overlooking a beach in a location easily accessible to the public. Using the cradle for image positioning, passers-by simply take a photo of the coast and upload it to a centralized database, which in turn provides a crowd-sourced record of coastline change over time. Behind this simple idea are advanced image processing algorithms that then enable the shoreline position (and other coastal features) to be mapped from the community snapshots in a scientifically rigorous manner. First established in Sydney, Australia in 2017, the network of CoastSnap stations has grown rapidly over the past five years to now encompass 200 monitoring locations in 21 countries. Analysis of the 44 Australian stations managed by the Authors indicates strong community participation, with over 10,000 images and 4000 community participants to date and an image submission frequency ranging from approximately weekly to daily (average = 2.6 images/station/week). Example practical applications of CoastSnap include: as a tool to monitor high-frequency shoreline change and coastal inlet dynamics; to support conservation efforts on protected coastlines; and to directly inform the timing of dredging and beach nourishment activities. This paper describes the background and evolution of the project and discusses its successes, challenges as well as future directions.

Coastal storms cause widespread damage to property, infrastructure, economic activity, and the environment. Along open sandy coastlines, two of the primary coastal storm hazards are coastal flooding by elevated ocean water levels and beach erosion as the result of storm wave action. At continental margins characterized by a shallow, wide continental shelf, coastal storms are more commonly associated with amplified storm surge and the damaging impacts caused by flooding of low-lying land. In contrast, along margins where the continental shelf is narrow and deep, coastal storm impacts are more often characterized by beach erosion, due to the typically lower magnitude of storm surge but a higher proportion of deepwater wave energy reaching the shoreline. A new Storm Hazard Matrix is presented that integrates these two distinct but inherently linked open coast hazards. The approach is based on the combination of two hazard scales. The first is a ¿coastal flooding hazard scale¿ that follows an established framework in which hazards are predominately driven by the vertical increase in ocean water levels during storms and any significant morphological changes caused by the storm are inferred. The second is a storm wave ¿beach erosion hazard scale¿ where hazards are predominately determined by the horizontal recession of the sandy beach and dune without necessarily large increases in water levels. The resulting framework comprises a total of sixteen unique combinations of flooding/erosion storm hazard regimes, each potentially requiring different disaster risk reduction approaches. Real-world application of the Storm Hazard Matrix is explored at contrasting coastlines for two major storm events, encompassing an extratropical cyclone that impacted the coastline of southeast Australia in June 2016, and a large hurricane (Hurricane Ivan) that impacted the Gulf Coast of the United States in 2004. The new approach identifies and distinguishes between the severity of localized coastal flooding and/or coastal erosion, and also provides enhanced insight to the nature, magnitude and alongshore variation of coastal storm hazards along the impacted coastline. Within the context of disaster risk reduction, preparedness and operational early warning, implementation of the Storm Hazard Matrix has the potential to deliver robust evaluations of storm hazards spanning a wider variety of both wave-dominated and surge-dominated coasts.

We present the result of a collaborative priority setting exercise to identify emerging issues and priorities in coastal geoscience and engineering (CGE). We use a ranking process to quantify the criticality of each priority from the perspective of Australian CGE researchers and practitioners. 74 activities were identified across seven categories: Data Collection and Collation, Coastal Dynamics and Processes, Modelling, Engineering Solutions, Coastal Hazards and Climate Change, Communication and Collaboration, and Infrastructure, Innovation, and Funding. We found consistent and unanimous support for the vast majority of priorities identified by the CGE community, with 91% of priorities being allocated a score of = 3 out of 5 (i.e., above average levels of support) by = 75% of respondents. Data Collection and Collation priorities received the highest average score, significantly higher than four of the other six categories, with Coastal Hazards and Climate Change the second ranked category and Engineering Solutions the lowest scoring category. Of the 74 priorities identified, 11 received unified and strong support across the CGE community and indicate a critical need for: additional coastal data collection including topographic and bathymetric, hydrodynamic, oceanographic, and remotely sensed data; improved data compilation and access; improved understanding of extreme events and the quantification of future impacts of climate change on nearshore dynamics and coastal development; enhanced quantification of shoreline change and coastal inundation processes; and, additional funding to support CGE research and applications to mitigate and manage coastal hazards. The outcomes of this priority setting exercise can be applied to guide policy development and decision-making in Australia and jurisdictions elsewhere. Further, the research and application needs identified here will contribute to addressing key practical challenges identified at a national level. CGE research plays a critical role in identifying and enabling social, environmental, and economic benefits through the proactive management of coastal hazard impacts and informed planning to mitigate the potential impacts of growing coastal risk, particularly in a changing climate. The prevalence and commonalities of the challenges faced by coastal communities globally due to increasing pressures from coastal hazards in a changing climate suggest that our findings will be applicable to other settings.

Citizen science is growing rapidly in Australia and globally, and presents valuable opportunities to engage with the community and amplify scientific research. The recent growth in citizen science is largely attributed to technology and has resulted in citizen science now recognised as having the potential to augment and enhance traditional scientific research and monitoring. Citizen science can deliver a level of spatial granularity often not possible with conventional research. This, coupled with its potential to engage the public meaningfully in science, uniquely positions citizen science to monitor and thereby effect genuine scientific outcomes. However, the rapid growth in citizen science has also resulted in some data and information challenges that need to be overcome. Here we present a general overview of citizen science and some of the opportunities and challenges associated with its rapid growth, with a focus on Australia. We use case studies of successful citizen science projects in New South Wales to demonstrate its potential across areas such as cost efficiency and scalability. Overall, these examples show how citizen science has the potential to provide a monumental shift in our ability to monitor the environment while simultaneously increasing understanding and trust in science within the broader community.

In 2017, the New South Wales (NSW) Office of Environment and Heritage (OEH) initiated a state-wide mapping program, SeaBed NSW, which systematically acquires high-resolution (2¿5 m cell size) multibeam echosounder (MBES) and marine LiDAR data along more than 2000 km of the subtropical-to-temperate southeast Australian continental shelf. This program considerably expands upon existing efforts by OEH to date, which have mapped approximately 15% of NSW waters with these technologies. The delivery of high volumes of new data, together with the vast repository of existing data, highlights the need for a standardised, automated approach to classify seabed data. Here we present a methodological approach with new procedures to semi-automate the classification of high-resolution bathymetry and intensity (backscatter and reflectivity) data into a suite of data products including classifications of seabed morphology (landforms) and composition (substrates, habitats, geomorphology). These methodologies are applied to two case study areas representing newer (Wollongong, NSW) and older (South Solitary Islands, NSW) MBES datasets to assess the transferability of classification techniques across input data of varied quality. The suite of seabed classifications produced by this study provide fundamental baseline data on seabed shape, complexity, and composition which will inform regional risk assessments and provide insights into biodiversity and geodiversity.