Timothy Ingleton

Dr. Timothy Ingleton

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Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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19 June 2015 in GigaScience
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Journal Article
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AKAnna Kopf
Anna Kopf
MBMesude Bicak
Mesude Bicak
RKRenzo Kottmann
Renzo Kottmann
JSJulia Schnetzer
Julia Schnetzer
IKIvaylo Kostadinov
Ivaylo Kostadinov
FGFrank Oliver Glöckner
Frank Oliver Glöckner
Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapsho

22 March 2019 in Geosciences
Verified
Journal Article
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MLMichelle Linklater
Michelle Linklater
TITimothy Ingleton
Timothy Ingleton
MKMichael Kinsela
Michael Kinsela
BMBradley D. Morris
Bradley D. Morris
KAKatie M. Allen
Katie M. Allen
DHDavid Hanslow
David Hanslow
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.

12 February 2024 in Scientific Data
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Journal Article
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MKMichael Kinsela
Michael Kinsela
BMBradley D. Morris
Bradley D. Morris
TITimothy Ingleton
Timothy Ingleton
TDThomas B. Doyle
Thomas B. Doyle
MSMichael D. Sutherland
Michael D. Sutherland
DHDavid Hanslow
David Hanslow
Wind wave observations in shallow coastal waters are essential for calibrating, validating, and improving numerical wave models to predict sediment transport, shoreline change, and coastal hazards such as beach erosion and oceanic inundation. Although ocean buoys and satellites provide near-global coverage of deep-water wave conditions, shallow-water wave observations remain sparse and often inaccessible. Nearshore wave conditions may vary considerably alongshore due to coastline orientation and shape, bathymetry and islands. We present a growing dataset of in-situ wave buoy observations from shallow waters (<35 m) in southeast Australia that comprises over 7,000 days of measurements at 20 locations. The moored buoys measured wave conditions continuously for several months to multiple years, capturing ambient and storm conditions in diverse settings, including coastal hazard risk sites. The dataset includes tabulated time series of spectral and time-domain parameters describing wave height, period and direction at half-hourly temporal resolution. Buoy displacement and wave spectra data are also available for advanced applications. Summary plots and tables describing wave conditions measured at each location are provided.

27 May 2020 in Estuaries and Coasts
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Journal Article
Open access
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MKMichael Kinsela
Michael Kinsela
DHDavid Hanslow
David Hanslow
Rafael CarvalhoRafael Carvalho
Rafael Carvalho
MLMichelle Linklater
Michelle Linklater
TITimothy Ingleton
Timothy Ingleton
CWColin D. Woodroffe
Colin D. Woodroffe
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.

7 April 2022 in Scientific Data
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Journal Article
Open access
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MRMoninya Roughan
Moninya Roughan
MHMichael Hemming
Michael Hemming
ASAmandine Schaeffer
Amandine Schaeffer
TATim Austin
Tim Austin
HBHelen Beggs
Helen Beggs
KRKen Ridgway
Ken Ridgway
Multi-decadal ocean time-series are fundamental baselines for assessing the impacts of environmental change, however, compiling and quality controlling historic data from multiple sources remains challenging. Here we aggregate, document, and release a number of long time-series temperature products and climatologies compiled from data obtained at 4 monitoring sites around Australia where sub-surface ocean temperature has been recorded nominally weekly to monthly since the 1940s/50s. In recent years, the sampling was augmented with data obtained from moored sensors, vertical profiles and satellite-derived data. The temperature data have been quality controlled, and combined using a rigorously tested methodology. We have packaged the multi-decadal, multi-depth, multi-platform temperature time-series at each site and produced a range of daily temperature climatologies from different data combinations and time periods. The 17 data products are provided as CF-compliant NetCDF files and will be updated periodically. The long-term temperature time-series will be useful for studies of ocean temperature variability, trends, anomalies and change. The data collection is supported by Australia’s Integrated Marine Observing System and data are open-access.

22 January 2024 in Nature Communications
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Journal Article
Open access
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NMNeil Malan
Neil Malan
MRMoninya Roughan
Moninya Roughan
MHMichael Hemming
Michael Hemming
TITimothy Ingleton
Timothy Ingleton
During 2022, extreme rainfall occurred across southeast Australia, making it the wettest year on record. The oceanic impact of extreme rainfall events in normally ‘dry’ regions is not well understood, as their effects are challenging to observe. Here, we use unique multi-platform timeseries and spatial data from 36 autonomous ocean glider missions over 13 years, and we define an extreme salinity threshold inshore of the East Australian Current. We show that the freshwater plume extended fivefold further than previously thought. The compound effect of multiple large rainfall events resulted in a newly observed stratification (‘double-stacking’) dynamic, with the stratification being largely controlled by salinity. Extreme salinity events are known to be important for species composition of local fisheries as well as detrimental for coastal water quality. Such events and their impacts may become more common as extreme rainfall events are projected to become more frequent in a changing climate. Hence, comprehensive observing strategies facilitating identification of salinity extremes are essential.