Abstract: Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.
Abstract: The main purpose of this study is to assess the
sediment quality and potential ecological risk in marine sediments in
Gymea Bay located in south Sydney, Australia. A total of 32 surface
sediment samples were collected from the bay. Current track
trajectories and velocities have also been measured in the bay. The
resultant trace elements were compared with the adverse biological
effect values Effect Range Low (ERL) and Effect Range Median
(ERM) classifications. The results indicate that the average values of
chromium, arsenic, copper, zinc, and lead in surface sediments all
reveal low pollution levels and are below ERL and ERM values. The
highest concentrations of trace elements were found close to
discharge points and in the inner bay, and were linked with high
percentages of clay minerals, pyrite and organic matter, which can
play a significant role in trapping and accumulating these elements.
The lowest concentrations of trace elements were found to be on the
shoreline of the bay, which contained high percentages of sand
fractions. It is postulated that the fine particles and trace elements are
disturbed by currents and tides, then transported and deposited in
deeper areas. The current track velocities recorded in Gymea Bay had
the capability to transport fine particles and trace element pollution
within the bay. As a result, hydrodynamic measurements were able to
provide useful information and to help explain the distribution of
sedimentary particles and geochemical properties. This may lead to
knowledge transfer to other bay systems, including those in remote
areas. These activities can be conducted at a low cost, and are
therefore also transferrable to developing countries. The advent of
portable instruments to measure trace elements in the field has also
contributed to the development of these lower cost and easily applied
methodologies available for use in remote locations and low-cost
economies.