Knowledge of the extreme ocean climate is essential for the accurate assessment of coastal hazards to facilitate risk informed decision making in coastal planning and management.Clustered storm events, where two or more storms occur within a relatively short space of time, may induce disproportionately large coastal erosion compared to non-clustered storm events.Therefore this study aims to develop a statistical approach to modelling the frequency and intensity of storm events on the eastern and southern coast of Australia, with a focus on examining storm clustering.This paper presents the preliminary analysis of the recently developed methods and results when they are applied to a study site on the central coast of New South Wales, Australia.This study is a key component of the Bushfire and Natural Hazards CRC Project "Resilience to clustered disaster events on the coast -storm surge" that aims to develop a new method to quantify the impact of coincident and clustered disaster events on the coast.Extreme storm events at a given site can be described using multivariate summary statistics, including the events' maximum significant wave height (Hsig), median wave period, median wave direction, duration, peak storm surge, and time of occurrence.This requires a definition of individual storm events, so the current methodology firstly involves the extraction of storm events from a 30-year timeseries of observations.Events are initially defined using a peaks-over-threshold approach based on the significant wave height with the 95% exceedance quantile (2.93 m) adopted as the threshold.Subsequently, these events are manually checked against sea-level pressure data to examine if closely spaced events are generated by the same meteorological system, and if so the events are combined.This means that the final event set is more likely to consist of meteorologically independent storm events.Various statistical techniques are applied to model the magnitude and frequency of the extracted storm events.A number of variations on the non-homogenous Poisson process model are developed to estimate the event occurrence rate, duration and spacing.The models account for the sub-annual variations in the occurrence rate, temporal dependency between successive events, and the finite duration of events.The results indicate that in the current dataset, closely spaced events are more temporally spread out than would be expected if the event timings are independent, which we term anti-clustering.A particular marginal distribution is fitted to each variable, i.e. a Generalised Pareto (GP) distribution for Hsig, and Pearson type 3 (PE3) distributions for duration and tidal residual.Empirical marginal distributions are employed for wave period and direction.The joint cumulative distribution function of all storm magnitude statistics is modelled by constructing the dependency structure using Copula functions.Two methods are tested: a t-copula and a combination of a Gumbel and Gaussian copulas.Comparison of modelled and observed scatterplots shows similar patterns.Goodness-of-fit tests such as Komologorov-Smirnov (K-S) tests, Chi-square tests and AIC and BIC are used to quantitatively evaluate the fitting qualities and to assess model parsimony, along with graphical visualisations, e.g.QQ plots.Based on this approach, a long-term synthetic time-series of storm events (10 6 years) is generated using the event magnitude and timing simulated with the fitted models.These long-term synthetic events can be used to derive exceedance probabilities and to construct designed storm events to be applied to beach erosion modelling.
SummaryWe present results of 334 ultra-wide band MT stations across an area of 100 km × 100 km in the prospective eastern Gawler Craton. The survey area is situated ~100 km south of the supergiant Olympic Dam IOCG deposit, across an area of several IOCG deposits and prospects, including Carrapateena, Oak Dam, and Khamsin. Station spacing varies between 5 km and reduces to 1.5 km around areas of known IOCG prospects. The 3D resistivity models show a north-south oriented conductor in the upper crust. Known IOCG prospects are situated along its margins. These results expand the previously only 2D defined signatures of IOCG deposits, such as Olympic Dam to the full 3D domain. Together with the wider-spacedAusLAMP deployment and a 1.5km to 3 km spaced AEM survey, the survey is unique for imaging the whole-oflithosphere footprint of IOCG deposits under cover.
A prominent TE and TM mode split is observed in magnetotelluric (MT) data below 0.5 Hz collected in the Perth Basin over the Harvey Ridge, Western Australia. We investigate the causes of mode splitting and consider implications on inversion of the MT data to subsurface electrical conductivity distribution. Twenty-five broad-band MT stations were acquired and remote reference processing was completed to arrive at a data set located midway between the Darling Fault and the Indian Ocean. We used forward modelling to test our strong suspicion that the Indian Ocean, Darling fault and architecture of the Granitic Basement were indeed the major contributors to mode splitting that we observed. Forward modelling of synthetic data was completed for comparison with the Harvey MT data. We were surprised at the match between synthetic and field data given the simplicity of the forward model and the considerable lateral distance between the MT soundings and the Indian Ocean or Darling fault. We were then able to make significant improvements to the MT inversion outcome by introducing a large scale geo-electrical architecture as the seed model for inversion. Our work demonstrates that large scale geo-electrical contrasts at considerable lateral distance from an MT transect, or the target zone need to be systematically introduced to the inversion if a quality outcome is to be achieved.
The characterisation of the thickness and geology of cover sequences significantly improves targeting for mineral exploration in buried terrains. Audio-frequency Magnetotelluric (AMT) data is applicable to characterise cover sequences, where their conductivity (inverse resistivity) can be differentiated. We present a regional study from the under-cover East Tennant region in the Northern Territory (Australia) where we have applied deterministic and probabilistic inversion methods to derive 2D and 1D resistivity models. We integrated these models with information of co-located basement penetrating boreholes (lithological and geophysical logs) to ground-truth and validate the models and to improve geophysical interpretations. In the East Tennant region, borehole lithology and wireline logging demonstrate that the modelled AMT response is largely controlled by the mineralogy of the cover and basement rocks. The bulk conductivity is due primarily to bulk mineralogy and the success of using the AMT models to predict cover thickness is shown to be dependent on whether the bulk mineralogy of cover and basement rocks are sufficiently different to provide a detectable conductivity contrast. Our investigation of a range of geological scenarios that differ in thickness, complexity and geology of the cover and basement rocks suggests that in areas where there is sufficient difference in bulk mineralogy and where the stratigraphy is relatively simple, AMT models predict the cover thickness with high certainty. In more complex scenarios interpretation of AMT models may be more ambiguous and requires integration with other data (e.g. drilling, wireline logging, potential field modelling). Overall, we conclude that the application of the method has been validated and the results compare favourably with borehole stratigraphy logs once geological (i.e. bulk mineralogical) complexity is understood. This demonstrates that the method is capable of identifying major litho-stratigraphic units with resistivity contrasts. Our results have assisted with the planning of regional drilling programs and have helped to reduce the uncertainty and risk associated with intersecting targeted stratigraphic units in covered terrains.
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