The Palm Valley oasis in arid central Australia is characterised by stands of palm trees (Livistona mariae). How these unique plants, separated by nearly a 1000 kilometres of arid country from their nearest relatives persist, has long fascinated visitors. Defining the hydrogeology of the Hermannsburg Sandstone, a regionally extensive and thick Devonian sequence of the Amadeus Basin that underlies Palm Valley, is the major thrust of investigation. Appraisal of drilling data shows this aquifer to be a dual porosity fractured rock aquifer which, on a regional scale, behaves as a low permeability, hydraulically continuous resource. Groundwater is low salinity (TDS &lt1000 mg/L) and bicarbonate rich. Slight variations in cation chemistry indicate different flow paths with separate geochemical histories have been sampled. Stable isotope (????H, ???????O) results from Palm Valley show groundwater to have a uniform composition that plots on or near a local meteoric water line. Radiocarbon results are observed to vary from effectively dead (&lt 4%) to 87 % modern carbon. To resolve groundwater age beyond the radiocarbon window the long lived radioisotope 36Cl was also used. Ratios of 36Cl/Cl range from 130 to 290 x 10-15. In this region atmospheric 36Cl/Cl ratio is around 300 x 10-15. Thus an age range of around 300 ka is indicated if, as is apparent, radioactive decay is the only significant cause of 36Cl/Cl variation within the aquifer. A review of previous, often controversial, 36Cl decay studies shows results are usually ambiguous due to lack of certainty when factoring subsurface Cl- addition into decay calculations. Apparently, due to the thickness of the Hermannsburg Sandstone, no subsurface sources of Cl- such as aquitards or halites, are encountered along groundwater flow paths, hence the clear 36Cl decay trend seen. The classic homogenous aquifer with varying surface topography, the &quotToth&quot flow model, is the simplest conceptual model that need be invoked to explain these isotope data. Complexities, associated with local topography flow cells superimposed on the regional gradient, signify groundwater with markedly different flow path lengths has been sampled. The long travel times (&gt 100 ka) indicate groundwater discharge would endure through arid phases associated with Quaternary climate oscillations. Such a flow system can explain the persistence of this arid zone groundwater-dependent ecosystem and highlight the possibility that Palm Valley has acted as a flora refuge since at least the mid- Pleistocene.

The Palm Valley oasis in arid central Australia is characterised by stands of palm trees (Livistona mariae). How these unique plants, separated by nearly a 1000 kilometres of arid country from their nearest relatives persist, has long fascinated visitors. Defining the hydrogeology of the Hermannsburg Sandstone, a regionally extensive and thick Devonian sequence of the Amadeus Basin that underlies Palm Valley, is the major thrust of investigation. Appraisal of drilling data shows this aquifer to be a dual porosity fractured rock aquifer which, on a regional scale, behaves as a low permeability, hydraulically continuous resource. Groundwater is low salinity (TDS &lt1000 mg/L) and bicarbonate rich. Slight variations in cation chemistry indicate different flow paths with separate geochemical histories have been sampled. Stable isotope (????H, ???????O) results from Palm Valley show groundwater to have a uniform composition that plots on or near a local meteoric water line. Radiocarbon results are observed to vary from effectively dead (&lt 4%) to 87 % modern carbon. To resolve groundwater age beyond the radiocarbon window the long lived radioisotope 36Cl was also used. Ratios of 36Cl/Cl range from 130 to 290 x 10-15. In this region atmospheric 36Cl/Cl ratio is around 300 x 10-15. Thus an age range of around 300 ka is indicated if, as is apparent, radioactive decay is the only significant cause of 36Cl/Cl variation within the aquifer. A review of previous, often controversial, 36Cl decay studies shows results are usually ambiguous due to lack of certainty when factoring subsurface Cl- addition into decay calculations. Apparently, due to the thickness of the Hermannsburg Sandstone, no subsurface sources of Cl- such as aquitards or halites, are encountered along groundwater flow paths, hence the clear 36Cl decay trend seen. The classic homogenous aquifer with varying surface topography, the &quotToth&quot flow model, is the simplest conceptual model that need be invoked to explain these isotope data. Complexities, associated with local topography flow cells superimposed on the regional gradient, signify groundwater with markedly different flow path lengths has been sampled. The long travel times (&gt 100 ka) indicate groundwater discharge would endure through arid phases associated with Quaternary climate oscillations. Such a flow system can explain the persistence of this arid zone groundwater-dependent ecosystem and highlight the possibility that Palm Valley has acted as a flora refuge since at least the mid- Pleistocene.

Hydrological observations are characterised by wet and dry cycles, a characteristic that is termed hydrological persistence. Interactions between global climate phenomena and the hydrological cycle result in rainfall and streamflow data clustering into wetter and drier states. These states have implications for the management and planning of water resources. Statistical tests constructed from the theory of wet and dry spells indicate that evidence for persistence in monthly observations is more compelling than at an annual scale. This thesis demonstrates that examination of monthly data yields spatially - consistent patterns of persistence across a range of hydrological variables. It is imperative that time series models for rainfall and streamflow replicate the observed fluctuations between the climate regimes. Monthly time series are generally represented with linear models such as ARMA variants ; however simulations from such models may underestimate the magnitude and frequency of persistence. A different approach to modelling these data is to incorporate shifting levels in the broader climate with a tendency to persist within these regimes. Hidden Markov models ( HMMs ) provide a strong conceptual basis for describing hydrological persistence, and are shown to provide accurate descriptions of fluctuating climate states. These models are calibrated here with a full Bayesian approach to quantify parameter uncertainty. A range of novel variations to standard HMMs are introduced, in particular Autoregressive HMMs and hidden semi - Markov models which have rarely been used to model monthly rainfall totals. The former model combines temporal persistence within observations with fluctuations between persistent climate states, and is particularly appropriate for modelling streamflow time series. The latter model extends the modelling capability of HMMs by fitting explicit probability distributions for state durations. These models have received little attention for modelling persistence at monthly scale. A non - parametric ( NP ) HMM, which overcomes the major shortcomings of standard parametric HMMs, is also described. Through removing the requirement to assume parametric forms of conditional distributions prior to model calibration, the innovative NP HMM framework provides an improved estimation of persistence in discrete and continuous data that remains unaffected by incorrect parametric assumptions about the state distributions. Spatially - consistent persistence is identified across Australia with the NP HMM, showing a tendency toward stronger persistence in low-rainfall regions. Coherent signatures of persistence are also identified across time series of total monthly rainfall, numbers of rain - days each month, and the intensities of the most extreme rain events recorded each month over various short durations, illustrating that persistent climate states modulate both the numbers of rain events and the amount of moisture contained within these events. These results provide a new interpretation of the climatic interactions that underlie hydrological persistence. The value of HMMs to water resource management is illustrated with the accurate simulation of a range of hydrologic data, which in each case preserves statistics and spell properties over a range of aggregations. Catchment - scale rainfall for the Warragamba Reservoir is simulated accurately with HMMs, and rainfall - runoff transformations from these simulations provide reservoir inflows of lower drought risk than provided from ARMA models. / Thesis (Ph.D.)--School of Civil and Environmental Engineering, 2006.

Hydrological observations are characterised by wet and dry cycles, a characteristic that is termed hydrological persistence. Interactions between global climate phenomena and the hydrological cycle result in rainfall and streamflow data clustering into wetter and drier states. These states have implications for the management and planning of water resources. Statistical tests constructed from the theory of wet and dry spells indicate that evidence for persistence in monthly observations is more compelling than at an annual scale. This thesis demonstrates that examination of monthly data yields spatially - consistent patterns of persistence across a range of hydrological variables. It is imperative that time series models for rainfall and streamflow replicate the observed fluctuations between the climate regimes. Monthly time series are generally represented with linear models such as ARMA variants ; however simulations from such models may underestimate the magnitude and frequency of persistence. A different approach to modelling these data is to incorporate shifting levels in the broader climate with a tendency to persist within these regimes. Hidden Markov models ( HMMs ) provide a strong conceptual basis for describing hydrological persistence, and are shown to provide accurate descriptions of fluctuating climate states. These models are calibrated here with a full Bayesian approach to quantify parameter uncertainty. A range of novel variations to standard HMMs are introduced, in particular Autoregressive HMMs and hidden semi - Markov models which have rarely been used to model monthly rainfall totals. The former model combines temporal persistence within observations with fluctuations between persistent climate states, and is particularly appropriate for modelling streamflow time series. The latter model extends the modelling capability of HMMs by fitting explicit probability distributions for state durations. These models have received little attention for modelling persistence at monthly scale. A non - parametric ( NP ) HMM, which overcomes the major shortcomings of standard parametric HMMs, is also described. Through removing the requirement to assume parametric forms of conditional distributions prior to model calibration, the innovative NP HMM framework provides an improved estimation of persistence in discrete and continuous data that remains unaffected by incorrect parametric assumptions about the state distributions. Spatially - consistent persistence is identified across Australia with the NP HMM, showing a tendency toward stronger persistence in low-rainfall regions. Coherent signatures of persistence are also identified across time series of total monthly rainfall, numbers of rain - days each month, and the intensities of the most extreme rain events recorded each month over various short durations, illustrating that persistent climate states modulate both the numbers of rain events and the amount of moisture contained within these events. These results provide a new interpretation of the climatic interactions that underlie hydrological persistence. The value of HMMs to water resource management is illustrated with the accurate simulation of a range of hydrologic data, which in each case preserves statistics and spell properties over a range of aggregations. Catchment - scale rainfall for the Warragamba Reservoir is simulated accurately with HMMs, and rainfall - runoff transformations from these simulations provide reservoir inflows of lower drought risk than provided from ARMA models. / Thesis (Ph.D.)--School of Civil and Environmental Engineering, 2006.