ALBERT

Description: Schlumberger’s modular dynamics tester (MDT) tool was used to test 10 Miocene sands in the Tubular Bells deep water oil field, offshore Gulf of Mexico, United States. Nine sands from true vertical depths of 19,999–26,464 ft (6096–8066 m) were sampled from a single well and another deeper sand (29,075 ft [8,862 m]) from a second well. Using ion and strontium, oxygen, and hydrogen isotopic analysis, the nine MDT water samples were demonstrated to be mostly formation water. The sample in the second well from 29,075 ft (8862 m) is filtrate, based on its oxygen and hydrogen isotopic composition (–4.10 and –26.3, standard mean ocean water [SMOW]). Insufficient water was recovered for ionic analysis, which made the isotopic analysis even more important to help document the origin of the water in what appears to be a hydrocarbon-charged interval. Using a combination of chemical and isotopic analyses, it is concluded that only two of the sands are possibly in fluid communication or separated by baffles. The other sands are each in separate fluid compartments. The salinity (total dissolved solids) of the formation waters decreases with depth and distance from the salt and ranges from approximately 39,000 to more than 288,000 mg/L. The formation waters have oxygen and hydrogen isotopic compositions ranging from +3.19 to +4.52 and –16.1 to –19.4, respectively (SMOW). Bromide–chloride systematics indicate that the formation waters are mixtures of normal seawater and seawater that was evaporated to and probably beyond halite saturation. The evaporite water is sourced from the deeper Jurassic section (Louann Salt) and likely came up along the salt–sediment interface along faults and fractures associated with emplacement of the salt stock and canopy. The formation waters were subsequently enriched in chloride and sodium to varying degrees by dissolution of the diapiric salt. Strontium isotopes are compatible with mixing of highly concentrated (evaporative) Jurassic seawater with relatively low 87 Sr/ 86 Sr ratios and much less concentrated (almost seawater salinity) pore water with more radiogenic strontium, the latter derived from silicate reactions during burial diagenesis. Short-chain organic acids are present in high concentrations (〉1000 mg/L) along with the organophilic ions boron and iodide. The concentrations of boron, iodide, and organic acids do not correlate with salinity. Boron and iodide show a strong positive relationship with each other and a less strong, but positive, relationship with organic acid concentrations. Boron and iodide are nearly twice as concentrated in waters of oil-bearing sands than in water-bearing sands and appear to be indicators of hydrocarbon proximity. One water-bearing sand has concentrations of boron and iodide as high as those seen in oil-bearing sands, possibly suggesting an updip oil accumulation.

Description: Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Description: In this paper, a disaggregation approach is suggested for the task of modelling hydrological responses within a spatially and temporally variable environment. With such an approach, large-scale environmental characteristics are tested for their ability to provide insight into the dominant physical mechanisms responsible for observed catchment responses. Using a regional-scale catchment in eastern Australia as a case study, the approach is firstly used to determine the utility of physical catchment data, and its organization in space, to provide insight into the compartmentalization of soil water storage within the catchment. In a second application, temporal disaggregation of the rainfall-runoff record into the cold-wet and warm-dry phases of the El Nino/Southern Oscillation (ENSO) phenomenon is utilized to provide an objective comparison between alternative model structures, based on the 'consistency' of model parameters in describing the effect of ENSO phase on water yield. Finally, combining the improved spatial representation of hydrological response with the model structure identified by temporal analysis is shown to result in a predictive framework whose level of uncertainty is lower than either of the individual strategies, and whose responses are consistent with the available evidence. It is noted that such modelling insight is unlikely to have been gained with traditional modelling strategies that seek to force a predetermined model structure to 'fit' the observed data. Copyright © 2002 John Wiley and Sons, Ltd.

Description: In this study, it is shown that the complexity of Soil Vegetation Atmosphere Transfer (SVAT) models leads to an equifinality of functional behaviour - many parameterizations from many areas of the parameter space lead to very similar responses. Individual parameters derived by calibration (i.e. model inversion) against limited measurements are, therefore, highly uncertain. Due to the non-linear internal behaviour of SVAT models, aggregation of uncertainly known parameter fields to parameterize landscape scale variability in surface fluxes will yield highly uncertain predictions. A disaggregation approach suggested by Beven (1995) requires that the land surface be represented by a linear sum of a number of representative parameterizations or functional types. This study explores the nature of the parameter space in terms of a simple definition of functional behaviour. Parameter interactions producing similar predicted behaviours are investigated through application of Principal Component Analyses. These reveal the lack of a dominant global interaction indicating the presence of highly complex parameter interactions throughout the feasible parameter space.

Description: The flow records of arid zone rivers are characterised by a high degree of seasonal variability, being dominated by long periods of very low or zero flow. Discrete flow events in these rivers are influenced by aseasonal factors such as global climate forcings. The atmospheric circulations of the El-Niño Southern Oscillation (ENSO) have been shown to influence climate regimes across many parts of the world. Strong teleconnections between changing ENSO regimes and discharges are likely to be observed in highly variable arid zones. In this paper, the influence of ENSO mechanisms on the flow records of two arid zone rivers in each of Australia and Southern Africa are identified. ENSO signals, together with multi-decadal variability in their impact as identified through seasonal values of the Interdecadal Pacific Oscillation (IPO) index, are shown to influence both the rate of occurrence and the size of discrete flow episodes in these rivers. Keywords: arid zones, streamflow, spates, climate variability, ENSO, Interdecadal Pacific Oscillation, IPO

Description: It has previously been argued that current Soil Vegetation Atmosphere Transfer (SVAT) models are over-parameterised given the calibration data typically available. Using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology, multiple feasible model parameter sets are here conditioned on latent heat fluxes and then additionally on the sensible and ground heat fluxes at a single site in Amazonia. The model conditioning schemes were then evaluated with a further data set collected at the same site according to their ability to reproduce the latent, sensible and ground heat fluxes. The results indicate that conditioning the model on only the latent heat flux component of the energy balance does not constrain satisfactorily the predictions of the other components of the energy balance. When conditioning on all heat flux objectives, significant additional constraint of the feasible parameter space is achieved with a consequent reduction in the predictive uncertainty. There are still, however, many parameter sets that adequately reproduce the calibration/validation data, leading to significant predictive uncertainty. Surface temperature measurements, whilst also subject to uncertainty, may be employed usefully in a multi-objective calibration of SWAT models.

Description: Flood frequency analysis typically assumes that annual floods arise from a single distribution and are independent. However, there is significant evidence for the existence of persistent climate modes. Timescales associated with climate variability range from inter-annual through to longer, multi-decadal time scales. In the case of the Australian climate, previous studies of the Indian and Pacific Oceans have indicated marked multi-decadal variability in both mean Sea Surface Temperatures (SST) and typical circulation patterns. In this light, data from 40 stream gauges around New South Wales are examined to determine whether flood frequency data are indeed independent and distributed identically. Given likely correlation in flood records between gauges, an assessment of the regional significance of observed changes in flood frequency is required. To achieve this, flood observations are aggregated into a regional index. A simple non-parametric test is then employed to identify the timing and magnitude of any change in mean annual flood. Finally, it is shown that the identified change in flood frequency corresponds directly to an observed shift in SST and mean circulation. These results demonstrate the role of natural variability in climate parameters and the need for an improved conceptual framework for flood frequency estimation. Keywords: Floods, flood frequency, climate variability, IPO, PDO, climate change

Description: Characterising the development of evapotranspiration through time is a difficult task, particularly when utilising remote sensing data, because retrieved information is often spatially dense, but temporally sparse. Techniques to expand these essentially instantaneous measures are not only limited, they are restricted by the general paucity of information describing the spatial distribution and temporal evolution of evaporative patterns. In a novel approach, temporal changes in land surface temperatures, derived from NOAA-AVHRR imagery and a generalised split-window algorithm, are used as a calibration variable in a simple land surface scheme (TOPUP) and combined within the Generalised Likelihood Uncertainty Estimation (GLUE) methodology to provide estimates of areal evapotranspiration at the pixel scale. Such an approach offers an innovative means of transcending the patch or landscape scale of SVAT type models, to spatially distributed estimates of model output. The resulting spatial and temporal patterns of land surface fluxes and surface resistance are used to more fully understand the hydro-ecological trends observed across a study catchment in eastern Australia. The modelling approach is assessed by comparing predicted cumulative evapotranspiration values with surface fluxes determined from Bowen ratio systems and using auxiliary information such as in-situ soil moisture measurements and depth to groundwater to corroborate observed responses.

Description: Hydrological extremes are amongst the most devastating forms of natural disasters both in terms of lives lost and socio-economic impacts. There is consequently an imperative to robustly estimate the frequency and magnitude of hydrological extremes. Traditionally, engineers have employed purely statistical approaches to the estimation of flood risk. For example, for an observed hydrological timeseries, each annual maximum flood is extracted and a frequency distribution is fit to these data. The fitted distribution is then extrapolated to provide an estimate of the required design risk (i.e. the 1% Annual Exceedance Probability – AEP). Such traditional approaches are overly simplistic in that risk is implicitly assumed to be static, in other words, that climatological processes are assumed to be randomly distributed in time. In this study, flood risk estimates are evaluated with regards to traditional statistical approaches as well as Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) conditional estimates for a flood-prone catchment in eastern Australia. A paleo-reconstruction of pre-instrumental PDO/ENSO occurrence is then employed to estimate uncertainty associated with the estimation of the 1% AEP flood. The results indicate a significant underestimation of the uncertainty associated with extreme flood events when employing the traditional engineering estimates.