Creating communities and communicating science during COVID-19: From Coast2Coast to Coast2Cast.

The global COVID-19 pandemic has seen extended lockdowns, isolation periods and travel restrictions across many countries around the world since early 2020. Some countries, such as Australia and New Zealand, closed their international borders in early 2020 preventing researchers travelling to other parts of the world. To facilitate the exposure of our students' work, and for them to meet international researchers, as well as foster a sense of coastal community, we started a zoominar series (seminars via Zoom) in April 2020. The Coast2Coast zoominar series had therefore humble origins but we soon discovered that there was an appetite for more widely sharing science across the coastal research disciplines. The Coast2Coast zoominar grew rapidly, attracting researchers from many countries around the world who presented and attended fortnightly online seminars. In just one year and a half we had 38 presentations with roughly 1900 attendees, creating a sense of community and belonging for the researchers involved. In early 2021, two of the co-authors, Giovanni (GC) and Ana (AVC) decided to expand and take this sense of community further creating the Coast2Cast podcast series, where researchers are asked research and non-research questions. In only 7 months, the podcasts have attracted more than 3700 listeners. Importantly, while the main prerequisite was high-quality and impactful research, diversity and inclusion were also a priority in selecting and inviting speakers for the zoominars and guests for the podcast. Importantly, our survey results suggest that there is a place for online events similar to Coast2Coast and Coast2Cast in a pandemic-free future, and that the coastal community involved has greatly benefited from such initiatives.

High-resolution topographic surveying and change detection with the iPhone LiDAR.

This paper introduces a comprehensive protocol leveraging open-access techniques to create small- to medium-scale 3D representations of the environment by using iPhone and iPad light detection and ranging (LiDAR). The protocol focuses on two capabilities of the iPhone LiDAR. The first capability is 3D modeling: iPhone LiDAR rapidly generates detailed indoor and outdoor 3D models, providing insights into object size, volume and geometry. The second capability is change detection: the 3D models created by the LiDAR sensor can be used for precise measurement of changes over time. Compared to other 3D topographic surveying methods, this method is rapid, high resolution, low cost and easy to use. The protocol outlines iPhone LiDAR scanning practices, model export and change detection. The expected results after executing the protocol are (i) a detailed 3D model of a small- to medium-sized object or area of interest and (ii) a distance point cloud revealing change between two point clouds of the same object or area between different times. The entire protocol can be conducted within 2 h by anyone with an iPhone with the LiDAR sensor and a computer. This protocol empowers scientists, students and community members conducting research with a cheap, easy-to-use method for addressing a range of questions and challenges, thus benefiting experts and the broader community.

Blind testing of shoreline evolution models.

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

Extreme coastal erosion enhanced by anomalous extratropical storm wave direction.

Extratropical cyclones (ETCs) are the primary driver of large-scale episodic beach erosion along coastlines in temperate regions. However, key drivers of the magnitude and regional variability in rapid morphological changes caused by ETCs at the coast remain poorly understood. Here we analyze an unprecedented dataset of high-resolution regional-scale morphological response to an ETC that impacted southeast Australia, and evaluate the new observations within the context of an existing long-term coastal monitoring program. This ETC was characterized by moderate intensity (for this regional setting) deepwater wave heights, but an anomalous wave direction approximately 45 degrees more counter-clockwise than average. The magnitude of measured beach volume change was the largest in four decades at the long-term monitoring site and, at the regional scale, commensurate with that observed due to extreme North Atlantic hurricanes. Spatial variability in morphological response across the study region was predominantly controlled by alongshore gradients in storm wave energy flux and local coastline alignment relative to storm wave direction. We attribute the severity of coastal erosion observed due to this ETC primarily to its anomalous wave direction, and call for greater research on the impacts of changing storm wave directionality in addition to projected future changes in wave heights.

A multi-decade dataset of monthly beach profile surveys and inshore wave forcing at Narrabeen, Australia.

Long-term observational datasets that record and quantify variability, changes and trends in beach morphology at sandy coastlines together with the accompanying wave climate are rare. A monthly beach profile survey program commenced in April 1976 at Narrabeen located on Sydney's Northern Beaches in southeast Australia is one of just a handful of sites worldwide where on-going and uninterrupted beach monitoring now spans multiple decades. With the Narrabeen survey program reaching its 40-year milestone in April 2016, it is timely that free and unrestricted use of these data be facilitated to support the next advances in beach erosion-recovery modelling. The archived dataset detailed here includes the monthly subaerial profiles, available bathymetry for each survey transect extending seawards to 20 m water depth, and time-series of ocean astronomical tide and inshore wave forcing at 10 m water depths, the latter corresponding to the location of individual survey transects. In addition, on-going access to the results of the continuing monthly survey program is described.