1000 resultados para Streamflow - Australia


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This research is a case study of Dungalah, a river Europeans call the Murray which describes and accounts for the past, present and future experiences of Indigenous and non-Indigenous communities in their protection, use and management of the Dungalah and its surrounding land. It provides a snapshot of the experiences of the researcher, her family, friencds and the Yorta Yorta people, living with Dungalah.

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This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0-3 month lead time, compared to rainfall distribution.

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The Upper Roper River is one of the Australia’s unique tropical rivers which have been largely untouched by development. The Upper Roper River catchment comprises the sub-catchments of the Waterhouse River and Roper Creek, the two tributaries of the Roper River. There is a complex geological setting with different aquifer types. In this seasonal system, close interaction between surface water and groundwater contributes to both streamflow and sustaining ecosystems. The interaction is highly variable between seasons. A conceptual hydrogeological model was developed to investigate the different hydrological processes and geochemical parameters, and determine the baseline characteristics of water resources of this pristine catchment. In the catchment, long term average rainfall is around 850 mm and is summer dominant which significantly influences the total hydrological system. The difference between seasons is pronounced, with high rainfall up to 600 mm/month in the wet season, and negligible rainfall in the dry season. Canopy interception significantly reduces the amount of effective rainfall because of the native vegetation cover in the pristine catchment. Evaporation exceeds rainfall the majority of the year. Due to elevated evaporation and high temperature in the tropics, at least 600 mm of annual rainfall is required to generate potential recharge. Analysis of 120 years of rainfall data trend helped define “wet” and “dry periods”: decreasing trend corresponds to dry periods, and increasing trend to wet periods. The period from 1900 to 1970 was considered as Dry period 1, when there were years with no effective rainfall, and if there was, the intensity of rainfall was around 300 mm. The period 1970 – 1985 was identified as the Wet period 2, when positive effective rainfall occurred in almost every year, and the intensity reached up to 700 mm. The period 1985 – 1995 was the Dry period 2, with similar characteristics as Dry period 1. Finally, the last decade was the Wet period 2, with effective rainfall intensity up to 800 mm. This variability in rainfall over decades increased/decreased recharge and discharge, improving/reducing surface water and groundwater quantity and quality in different wet and dry periods. The stream discharge follows the rainfall pattern. In the wet season, the aquifer is replenished, groundwater levels and groundwater discharge are high, and surface runoff is the dominant component of streamflow. Waterhouse River contributes two thirds and Roper Creek one third to Roper River flow. As the dry season progresses, surface runoff depletes, and groundwater becomes the main component of stream flow. Flow in Waterhouse River is negligible, the Roper Creek dries up, but the Roper River maintains its flow throughout the year. This is due to the groundwater and spring discharge from the highly permeable Tindall Limestone and tufa aquifers. Rainfall seasonality and lithology of both the catchment and aquifers are shown to influence water chemistry. In the wet season, dilution of water bodies by rainwater is the main process. In the dry season, when groundwater provides baseflow to the streams, their chemical composition reflects lithology of the aquifers, in particular the karstic areas. Water chemistry distinguishes four types of aquifer materials described as alluvium, sandstone, limestone and tufa. Surface water in the headwaters of the Waterhouse River, the Roper Creek and their tributaries are freshwater, and reflect the alluvium and sandstone aquifers. At and downstream of the confluence of the Roper River, river water chemistry indicates the influence of rainfall dilution in the wet season, and the signature of the Tindall Limestone and tufa aquifers in the dry. Rainbow Spring on the Waterhouse River and Bitter Spring on the Little Roper River (known as Roper Creek at the headwaters) discharge from the Tindall Limestone. Botanic Walk Spring and Fig Tree Spring discharge into the Roper River from tufa. The source of water was defined based on water chemical composition of the springs, surface and groundwater. The mechanisms controlling surface water chemistry were examined to define the dominance of precipitation, evaporation or rock weathering on the water chemical composition. Simple water balance models for the catchment have been developed. The important aspects to be considered in water resource planning of this total system are the naturally high salinity in the region, especially the downstream sections, and how unpredictable climate variation may impact on the natural seasonal variability of water volumes and surface-subsurface interaction.

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The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system’s Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

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The predictability of a chaotic series is limited to a few future time steps due to its sensitivity to initial conditions and the exponential divergence of the trajectories. Over the years, streamflow has been considered as a stochastic system in many approaches. In this study, the chaotic nature of daily streamflow is investigated using autocorrelation function, Fourier spectrum, correlation dimension method (Grassberger-Procaccia algorithm) and false nearest neighbor method. Embedding dimensions of 6-7 obtained indicates the possible presence of low-dimensional chaotic behavior. The predictability of the system is estimated by calculating the system's Lyapunov exponent. A positive maximum Lyapunov exponent of 0.167 indicates that the system is chaotic and unstable with a maximum predictability of only 6 days. These results give a positive indication towards considering streamflow as a low dimensional chaotic system than as a stochastic system.

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An increase in plantation forestry has been linked to a reduction in streamflows in some catchments. Quantifying the relative contribution of this land-use change on streamflows can be complex when those changes occur during weather extremes such as drought. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to two sub-catchments in south-eastern Australia which have seen the introduction and establishment of plantation land use in the past 15 years, coinciding with severe drought (1997–2009). The models were both manually and auto-calibrated and produced very good fits to observed streamflow data during both calibration (1980–1991) and validation (1992–2009) periods. Sensitivity analyses indicated that the models were most sensitive to soil and groundwater parameterisation. Analysis of drought conditions on streamflows showed significant declines from long-term average streamflows, while assessment of baseflow contributions by the models indicated a mix of over- and underestimation depending on catchment and season. The modelled introduction of plantation forestry did not significantly change streamflows for a scenario which did not include the land-use change, suggesting that the modelled land-use change in the catchments was not sufficiently extensive to have an impact on streamflows despite simulating actual rates of change. The SWAT models developed by this study will be invaluable as a basis for future use in regional climate-change studies and for the assessment of land management and land-use change impact on streamflows.

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In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.