https://nova.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45908
This paper investigates the rates of SLR in two coastal lakes in NSW - Lake Macquarie and Lake Illawarra, the latter of which had entrance training completed in 2008. Tide gauge data is used to assess trends in exceedance probability values of low, median and high water levels represented by 95%, 50% and 5% exceedance probability respectively within coastal lakes and ocean conditions at Patonga for proxy. In addition, the relationship between coastal lake water levels and ENSO are investigated. Within Lake Macquarie both median and high water levels have shown significant increases, however, high water levels have shown the greatest increases most noticeable in the entrance channel at Swansea. This indicates increases in water level range and increased exposure to ocean tides and conditions. ENSO, represented by the Southern Oscillation Index (SOI) was shown to be responsible for up to 6% of water level variability within Lake Macquarie, highlighting the need to incorporate large-scale oscillations when assessing potential inundation hazards in these systems.

Lake Illawarra exhibited a response to entrance training through a significant increase in high water levels within the lake. Since entrance training, high water levels have increased at rate of up to 9.3 mm per year which is over three times the global SLR estimate. The minimal association between water level variation within Lake Illawarra and the SOI, together with increased water level ranges due to rapid annual increases in high water levels indicated a dynamic response to entrance training. This dynamic nature highlights the necessity of regular monitoring of SLR within the lake and robust inundation hazard modelling.]]> Tue 08 Nov 2022 09:25:08 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:45907 Tue 08 Nov 2022 09:18:06 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39957 th percentile of the maximum wave amplitudes (over time) of the relevant T2 scenario within each coastal zone (P95). Threshold values for P95 have previously been derived through analysis of observed impacts for recent events. Given that historical records are available for only a short time period and no observations exist for which a Land Threat would have been issued for Australia, it has been difficult to determine the appropriate threshold for a Land Threat. Several recent tsunami hazard assessment studies have used inundation models nested within T2 scenarios. These modelling results are used to evaluate the threshold values for JATWC tsunami warnings and provide guidance on a possible further warning tier - Major Land Threat. The optimum Land Threat threshold for P95 is found to be 48.5cm, however, it is not recommended that any changes are made from the existing operational threshold of 55cm. The optimum threshold for P95 a Major Land Threat is found to be 150.5 cm.]]> Tue 04 Oct 2022 15:13:11 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39866 Q_b) is a key parameter for parametric surf zone models. It is via this variable that these models control the energy dissipation in the surf zone. Historically, Q_b has been obtained using probability distribution functions (PDFs) of the wave height (p(H)). This paper describes an alternative, data-driven approach to obtaining the fraction of broken waves that is a significant improvement over the more traditional approaches. This new model is based on an ensemble of regression trees in which Q_b is learnt directly from an extensive field dataset. The ensemble uses three input parameters that are often available to coastal engineers: offshore significant wave height (𝐻_𝑚0∞), offshore peak wave period (𝑇_𝑚01∞), and time-averaged relative water depths relative to the mean sea level (h/𝐻_𝑚0∞), and predicts Q_b at an averaged given relative water depth. The results indicate that the model can predict the depth-dependent variability of Q_b with a high degree of accuracy (averaged r² ≥ 0.95, averaged root mean square error ≤ 0.05, averaged mean absolute error ≤ 0.04) in virtually no computational time. When compared to three widely used Q_b models that are derived from PDFs of the wave heights, the model developed here showed significant improvement with reductions in the errors (average error reduction of 25%) and significant improvement for r²-scores (average increase ≥ 30%). Although complex, the method developed here could be advantageous over the more traditional approach because of its high degree of precision and accuracy and because it does not depend on prior knowledge of p(H). In summary, the present model could be used as a replacement for the formulation of Q_b in parametric wave models, which should result in better overall predictions, and thus, in better coastal management tools.]]> Thu 21 Jul 2022 09:34:35 AEST ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:39858 Thu 21 Jul 2022 09:34:26 AEST ]]>