Australian utility weights for the EORTC QLU-C10D, a multi-attribute utility instrument derived from the cancer-specific quality of life questionnaire, EORTC QLQ-C30

Background: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely-used cancer-specific quality of life questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with 4 levels. To be used in cost-utility analysis, country-specific valuation sets are required. Objective: To provide Australian utility weights for the QLU-C10D. Methods: An Australian online panel was quota sampled to ensure population representativeness by sex and age (≥18y). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy. Results: 1979 panel members opted-in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death. Conclusions: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively

Impact of Coal Resource Development on Streamflow Characteristics: Influence of Climate Variability and Climate Change

The potential cumulative impact of coal mining and coal seam gas extraction on water resources and water-dependent assets from proposed developments in eastern Australia have been recently assessed through a Bioregional Assessment Programme. This study investigates the sensitivity of the Bioregional Assessment results to climate change and hydroclimate variability, using the Gloucester sub-region as an example. The results indicate that the impact of climate change on streamflow under medium and high future projections can be greater than the impact from coal mining development, particularly where the proposed development is small. The differences in the modelled impact of coal resource development relative to the baseline under different plausible climate futures are relatively small for the Gloucester sub-region but can be significant in regions with large proposed development. The sequencing of hydroclimate time series, particularly when the mine footprint is large, significantly influences the modelled maximum coal resource development impact. The maximum impact on volumetric and high flow variables will be higher if rainfall is high in the period when the mine footprint is largest, and vice-versa for low flow variables. The results suggest that detailed analysis of coal resource development impact should take into account climate change and hydroclimate variability

Reduced streamflow in water-stressed climates consistent with CO₂ effects on vegetation

Global environmental change has implications for the spatial and temporal distribution of water resources, but quantifying its effects remains a challenge. The impact of vegetation responses to increasing atmospheric CO₂ concentrations on the hydrologic cycle is particularly poorly constrained. Here we combine remotely sensed normalized difference vegetation index (NDVI) data and long-term water-balance evapotranspiration (ET) measurements from 190 unimpaired river basins across Australia during 1982–2010 to show that the precipitation threshold for water limitation of vegetation cover has significantly declined during the past three decades, whereas sub-humid and semi-arid basins are not only ‘greening’ but also consuming more water, leading to significant (24–28%) reductions in streamflow. In contrast, wet and arid basins show nonsignificant changes in NDVI and reductions in ET. These observations are consistent with expected effects of elevated CO₂ on vegetation. They suggest that projected future decreases in precipitation are likely to be compounded by increased vegetation water use, further reducing streamflow in water-stressed regions.4 page(s

Reduced streamflow in water-stressed climates consistent with CO₂ effects on vegetation

Global environmental change has implications for the spatial and temporal distribution of water resources, but quantifying its effects remains a challenge. The impact of vegetation responses to increasing atmospheric CO₂ concentrations on the hydrologic cycle is particularly poorly constrained. Here we combine remotely sensed normalized difference vegetation index (NDVI) data and long-term water-balance evapotranspiration (ET) measurements from 190 unimpaired river basins across Australia during 1982–2010 to show that the precipitation threshold for water limitation of vegetation cover has significantly declined during the past three decades, whereas sub-humid and semi-arid basins are not only ‘greening’ but also consuming more water, leading to significant (24–28%) reductions in streamflow. In contrast, wet and arid basins show nonsignificant changes in NDVI and reductions in ET. These observations are consistent with expected effects of elevated CO₂ on vegetation. They suggest that projected future decreases in precipitation are likely to be compounded by increased vegetation water use, further reducing streamflow in water-stressed regions.4 page(s

Use of AWRA-L and AWRA-R in the bioregional assessment program

The Australian government is undertaking a program of bioregional assessments (BAs) in order to better understand the potential impacts of coal seam gas (CSG) and large coal mining developments on water resources and water-related assets. The aim of the program is to strengthen the science underpinning decision making on CSG and large coal mining developments. A key component of this work is in providing credible, consistent estimates of the impact of CSG and coal mining developments on river flows. The aim of surface water modelling in bioregional assessments is to provide information on flow characteristics at locations in the stream networks that are relevant for key assets and receptors. In particular, the modelling needs to account for changes in flow regime that relate directly to the impacts of future coal mining and coal seam gas extraction. This paper reviews some of the candidate models for achieving these outcomes and outlines some of the practical considerations behind the resulting choice of modelling tools. AWRA-L and AWRA-R have been chosen as the modelling tools to generate these river flow responses. Fluxes from the landscape (predominantly surface runoff, interflow and baseflow) are modelled using AWRA-L. These fluxes are then accumulated and routed through the river network using AWRA-R

Modelling the cumulative impacts of future coal mining and coal seam gas extraction on river flows: applications of methodology

This manuscript presents examples of the modelling of the impacts of coal mining and coal seam gas extraction on streamflow in five study catchments in Australia. The manuscript includes details on data preparation and model set-up and calibration. The modelling methodology enables the prediction of cumulative impacts from multiple future coal resource developments and distributes these predictions at multiple locations in the landscape. It is framed in terms of a structured uncertainty analysis to provide information on the likelihoods and potential ranges of various impacts. Also included is a qualitative uncertainty analysis which subjectively assesses the likely impact on model results of various assumptions made during the modelling procedure. Model results suggest that, in the Australian context, maximum percentage reductions in annual streamflow are approximately commensurate with the proportion of coal mine coverage. In coal seam gas fields, reductions in annual streamflow are proportional to well density. The manuscript goes on to demonstrate how these modelling results can be used to identify a zone of potential hydrological change within a catchment. This zone delineates those parts of the landscape where water-dependent landscape classes and assets may be vulnerable to change associated with changes in the streamflow regime. A corollary of this is that any parts of the landscape outside the zone of potential hydrological change are unlikely to be affected by coal resource development

Progress in nitrogen deposition monitoring and modelling

The chapter reviews progress in monitoring and modelling of atmospheric nitrogen (N) deposition at regional and global scales. The Working Group expressed confidence in the inorganic N wet deposition estimates in U.S., eastern Canada, Europe and parts of East Asia. But, long-term wet or dry N deposition information in large parts of Asia, South America, parts of Africa, Australia/Oceania, and oceans and coastal areas is lacking. Presently, robust estimates are only available for inorganic N as existing monitoring generally does not measure the complete suite of N species, impeding the closing of the atmospheric N budget. The most important species not routinely measured are nitrogen dioxide (NO2), ammonia (NH3), organic N and nitric acid (HNO3). Uncertainty is much higher in dry deposition than in wet deposition estimates. Inferential modelling (combining air concentrations with exchange rates) and direct flux measurements are good tools to estimate dry deposition; however, they are not widely applied. There is a lack of appropriate parameterizations for different land uses and compounds for input into inferential models. There is also a lack of direct dry deposition flux measurements to test inferential models and atmospheric model estimates