Diatom assemblages in sandy deposits of the 2004 tsunami at Phra Thong Island, Thailand may provide clues to flow conditions during the tsunami. The tsunami deposits contain one or more beds that fine upward, commonly from medium sand to silty very fine sand. Diatom assemblages of the lowermost portion of the deposit predominantly comprise of unbroken beach and subtidal species that live attached to sand grains. The dominant taxa shift to marine plankton species in the middle of the bed and to a mix of freshwater, brackish, and marine species near the top. These trends are consistent with expected changes in current velocities of tsunami through time. During high current velocities, medium sand is deposited; only beach and subtidal benthic diatoms attached to sediment can be incorporated into the tsunami deposit. High shear velocity keeps finer material, including planktonic diatoms in suspension. With decreasing current velocities, finer material including marine plankton can be deposited. Finally, during the lull between tsunami waves, the entrained freshwater, brackish, and marine species settle out with mud and plant trash. Low numbers of broken diatoms in the lower medium sand implies rapid entrainment and deposition, whilst selective breakage of marine plankton (Thalassionema nitzschioides, and Thalassiosira and Coscinodiscus spp.) in the middle portion of the deposit probably results from abrasion in the turbulent current before deposition.

The variability in the inherent optical properties along an estuary-coast-ocean continuum in tropical Australia has been studied. The study area, the Fitzroy Estuary and Keppel Bay system, is a shallow coastal environment (depth < 30 m) with highly turbid waters in the estuary and blue oceanic waters in the bay and subject to macrotides. Biogeochemical and inherent optical properties (IOPs) were sampled in the near-surface layer spatially and across the tidal phase during the dry season. These determinations included continuous measurements of spectral absorption, scattering and backscattering coefficients, together with discrete measurements of spectral absorption coefficients of phytoplankton, nonalgal particles and colored dissolved organic matter, and concentrations of phytoplankton pigments and suspended matter. Because of a large variability in the characteristics of the water components on short spatial and temporal scales, we observe a large variability in the associated optical properties. From the estuary to the bay, particle scattering and dissolved absorption decreased by 2 orders of magnitude, and nonalgal particle absorption decreased by 3 orders of magnitude. We also observed a strong variability in particle single scattering albedo and backscattering efficiency (by a factor of 6) and in specific IOPs (IOPs normalized by the relevant constituent concentration) such as suspended matter-specific particle scattering and chlorophyll-specific phytoplankton absorption. Superimposed on this strong spatial variability is the effect of the semidiurnal tide, which affects the spatial distribution of all measured properties. These results emphasize the need for spatially and temporally adjusted algorithms for remote sensing in complex coastal systems.

The coastal zone is arguably the most difficult geographical region to capture as data because of its dynamic nature. Yet, coastal geomorphology is fundamental data required in studies of the potential impacts of climate change. Anthropogenic and natural structural features are commonly mapped individually, with their inherent specific purposes and constraints, and subsequently overlain to provide map products. This coastal geomorphic mapping project centered on a major coastal metropolitan area between Lake Illawarra and Newcastle, NSW, has in contrast classified both anthropogenic and natural geomorphological features within the one dataset to improve inundation modelling. Desktop mapping was undertaken using the Australian National Coastal Geomorphic (Polygon) Classification being developed by Geoscience Australia and supported by the Department of Climate Change. Polygons were identified from 50cm and 1m aerial imagery. These data were utilized in parallel with previous maps including for example 1:25K Quaternary surface geology, acid sulphate soil risk maps as well as 1:100K bedrock geology polygon maps. Polygons were created to capture data from the inner shelf/subtidal zone to the 10 m contour and include fluvial environments because of the probability of marine inundation of freshwater zones. Field validation was done as each desktop mapping section was near completion. This map has innovatively incorporated anthropogenic structures as geomorphological features because we are concerned with the present and future geomorphic function rather than the past. Upon completion it will form part of the National Coastal Geomorphic Map of Australia, also being developed by Geoscience Australia and utilized in conjunction with Smartline.

Monitoring changes in the spatial distribution and health of biotic habitats requires spatially extensive surveys repeated through time. Although a number of habitat distribution mapping methods have been successful in clear, shallow-water coastal environments (e.g. aerial photography and Landsat imagery) and deeper (e.g. multibeam and sidescan sonar) marine environments, these methods fail in highly turbid and shallow environments such as many estuarine ecosystems. To map, model and predict key biotic habitats (seagrasses, green and red macroalgae, polychaete mounds [Ficopamatus enigmaticus] and mussel clumps [Mytilus edulis]) across a range of open and closed estuarine systems on the south-west coast of Western Australia, we integrated post-processed underwater video data with interpolated physical and spatial variables using Random Forest models. Predictive models and associated standard deviation maps were developed from fine-scale habitat cover data. Models performed well for spatial predictions of benthic habitats, with 79-90% of variation explained by depth, latitude, longitude and water quality parameters. The results of this study refine existing baseline maps of estuarine habitats and highlight the importance of biophysical processes driving plant and invertebrate species distribution within estuarine ecosystems. This study also shows that machine-learning techniques, now commonly used in terrestrial systems, also have important applications in coastal marine ecosystems. When applied to video data, these techniques provide a valuable approach to mapping and managing ecosystems that are too turbid for optical methods or too shallow for acoustic methods.

Legacy product - no abstract available

To be completed

This dataset maps the geomorphic habitat environments (facies) for 36 South Australian coastal waterways. The classification system contains 12 easily identifiable and representative environments: Barrier/back-barrier, Bedrock, Central Basin, Channel, Coral, Flood- and Ebb-tide Delta, Fluvial (bay-head) Delta, Intertidal Flats, Mangrove, Rocky Reef, Saltmarsh/Saltflat, Tidal Sand Banks (and Unassigned). These types represent habitats found across all coastal systems in Australia. Most of the 36 coastal waterways have a "Modified" environmental condition (as opposed to "Near Pristine"), according to the National Land and Water Resources Audit definition.

This dataset maps the geomorphic habitat environments (facies) for 213 Queensland coastal waterways. This version of the dataset includes 73 newly mapped estuaries, classified as 'Near pristine'. The classification system contains 12 easily identifiable and representative environments: Barrier/back-barrier, Bedrock, Central Basin, Channel, Coral, Flood- and Ebb-tide Delta, Fluvial (bay-head) Delta, Intertidal Flats, Mangrove, Rocky Reef, Saltmarsh/Saltflat, Tidal Sand Banks (and Unassigned). These types represent habitats found across all coastal systems in Australia. Southern and central Great Barrier Reef lagoon coasts have a broad spectrum of river, tide and wave- dominated estuaries.

This dataset maps the geomorphic habitat environments (facies) for 88 Tasmanian coastal waterways. The classification system contains 11 easily identifiable and representative environments: Barrier/back-barrier, Bedrock, Central Basin, Channel, Coral, Flood- and Ebb-tide Delta, Fluvial (bay-head) Delta, Intertidal Flats, Rocky Reef, Saltmarsh/Saltflat, Tidal Sand Banks (and Unassigned). These types represent habitats found across all coastal systems in Australia. The majority of near pristine estuaries in Tasmania are located in the south and west of the State and on Cape Barren Island, according to the Department of Primary Industries, Water and Environment.

TBA