Rebecca Doble

Access to safe and reliable water is fundamental to human health and well-being and to achieving United Nations Sustainable Development Goal 6. Yet many remote Australian communities, including First Nations communities, face challenges in securing drinking water. Supplies do not consistently meet the Australian Drinking Water Guidelines, with adverse public-health and socio-economic consequences. Using a targeted literature search and narrative synthesis, this review integrates peer-reviewed literature, Australian government and utility reports, and technical case studies on drinking-water quality and decentralised treatment in remote Australia. Sources were selected for contextual relevance and analysed according to field performance, technology readiness, operational requirements and whole-of-life sustainability consideration. The review examines water-quality challenges and evaluates established and emerging treatment technologies for remote settings. Conventional approaches, including disinfection, filtration and desalination, provide proven treatment functions but may be constrained by isolation, harsh environmental conditions, ageing infrastructure and limited operation and maintenance capacity. Emerging technologies, including electrochemical processes, forward osmosis and membrane distillation, may offer context-specific advantages but lack long-term validation in remote Australian communities. A technology assessment framework guides selection of robust, adaptable and scalable solutions. The findings emphasise sustained community engagement, responsible resource stewardship, performance monitoring and maintenance, effective brine management and demonstrated technology readiness. Research and implementation priorities include emerging-technology field validation, advanced real-time monitoring, renewable-energy integration, and fit-for-purpose governance and investment models aligned with community priorities, institutional capacity, regulatory requirements and whole-of-life service delivery. These priorities would strengthen the reliability, resilience and long-term sustainability of remote drinking-water services.

To-date Australia has had mostly coastal occurrences in a small but growing number of species of high pathogenicity avian influenza (HPAI) H5N1 clade 2.3.4.4b. The potential impacts of expected spread are the focus of significant preparation activities. Here we report on early surveillance undertaken in 2025-26 in the Murray-Darling Basin, Australia’s largest river system, which contains internationally important wetlands that support large multi-species aggregations of waterbirds vulnerable to mass mortality. We detected two low pathogenicity avian influenza (LPAI) viruses of Australian origin in wild waterbirds. Ongoing surveillance will aid in early detection and rapid response in the case of a major inland outbreak of H5N1.

Wetlands are internationally recognised for their ecological, cultural, and economic significance, providing critical ecosystem services such as biodiversity conservation, water quality improvement, and flood regulation. However, wetlands often face compounding challenges from climate change and historical river regulation, creating complex and uncertain futures that demand innovative adaptation strategies. Anticipating and responding to these challenges is particularly difficult given the interplay between hydrological alterations, ecological thresholds, and cultural values.While models inform adaptation decisions, it is people who make them. Effective climate adaptation for wetlands hinges on matching assessment methods to problem complexity and co-producing solutions that integrate diverse knowledge systems. Despite substantial advances in modelling capabilities, critical gaps persist in translating outputs into actionable metrics for local management. Hydrological models often fail to capture complex, non-linear impacts, cumulative stressors, and higher-order system values such as connectivity and cultural-spiritual dimensions. Wetlands function as integrated socio-ecological systems, challenging the reductionist modelling approaches that decompose them into discrete components. Conversely, co-production of adaptation pathways required both local knowledge and evidence-based climate projections to provide a robust foundation for discussion and decision-making. Effective adaptation requires blending the best available science with local and Indigenous experiential knowledge, particularly for complex or chaotic impact pathways where historical analogues are absent.This research addressed some of these challenges through co-creation and integrating human and hydroecological systems for climate adaptation planning. The study developed climate vulnerability assessments and adaptation roadmaps for three Ramsar-listed wetlands in the Murray–Darling Basin, Australia: Riverland, Barmah Forest, and the Macquarie Marshes, through a multidisciplinary, participatory process involving over 160 local and regional land and water managers. The approach integrated hydroclimate projections with local knowledge and Indigenous cultural values, adapted from established climate risk frameworks for Australian Ramsar sites and World Heritage areas. Hydroclimate information was developed from the best available climate and hydrological model outputs, and included past and future temperatures, rainfall volumes and characteristics, river flows, and inundation dynamics, providing scientific evidence to underpin the co-development process. A list of core site values and features were co-produced with participants, and their vulnerability assessed using combined qualitative and quantitative analyses to explore ecological thresholds and climate responses. Using spatial and temporal climate analogues and hydrological projections, visions of a changed future site were articulated, and adaptation pathways were co-developed to guide management towards climate-ready objectives while acknowledging significant ecological transformation.By complementing quantitative modelling with participatory processes, this methodology fills a critical gap in adaptation research for complex ecosystems in highly regulated catchments. It offers a replicable framework for developing climate-ready management strategies that respect ecological integrity and cultural values while navigating some of the sources of uncertainty.

The Murray-Darling Basin (MDB) is a highly allocated and regulated, mostly semiarid basin in south-eastern Australia, where groundwater is a significant water resource. Future climate predictions for the MDB include an expansion of arid and semiarid climate zones to replace temperate areas. The impacts of climate change are already evident in declining groundwater levels and changes in the connection status between rivers and groundwater, and modelling has predicted a further reduction in future groundwater recharge and ongoing declines in groundwater levels. This is predicted to further reduce river baseflow and negatively impact groundwater-dependent ecosystems (GDEs), and these system responses to a changing climate and extreme events are complex and not always well understood. This report provides an overview of the current state of knowledge of groundwater response to a changing climate for the MDB, and outlines challenges and opportunities for future groundwater research and management. Opportunities for the region include improving data systems and acquisition through automation and novel data sources, and growing capability in integrated, risk-based modelling. Quantification of the groundwater/surface-water connection response to declining groundwater levels, and assessing GDE water requirements and thresholds, would enable identification of vulnerable systems and inform the development of metrics for adaptive management, improving the ability to respond to climate extremes. There is potential to adapt policy to support active management of groundwater where required, including conjunctive use and water banking. Improving knowledge sharing and water literacy, including understanding community values of groundwater and GDEs, would support future decision-making.

The Geological and Bioregional Assessment Program examines the potential impacts of shale, tight and deep coal gas development on water and the environment. A key part of the project was quantifying the potential for a decline in the water quality of unconfined aquifers due to unintentional chemical release at the soil surface. To assess this hazard, a quantitative analysis of chemical migration pathways was undertaken, which involved the estimation of contaminant attenuation by dilution and dispersion in soil and groundwater. This provided a conservative screening approach to identify areas for further analysis. Attenuation calculations involved one-dimensional advection-dispersion (AD) simulations through the unsaturated zone, and three-dimensional AD solute transport within the surficial aquifers. Dilution factor (DF) relationships for the combined effect of attenuation in the unsaturated and saturated zone were used to construct spatial maps of the potential for impact on aquifer properties after accidental chemical spills. A higher DF (therefore lower consequence of the surface contamination) was associated with deeper unsaturated zones characterized by heavier soils near the surface, and lower ground water velocities due to lower hydraulic conductivity and/or hydraulic gradient in the saturated zone. The framework was applied across the Cooper Basin and Beetaloo Sub-basin and resulted in two types of maps. The first identified areas being more susceptible to contamination if soil remediation does not occur within a 10-year period. The second map shows the spatially variable combined DFs for a ground water receptor, which may be used to develop site-specific management plans and mitigation measures.

The biophysical processes occurring in the unsaturated zone have a direct impact on the water table dynamics. Representing these processes through the application of unsaturated zone models of different complexity has an impact on the estimates of the volumes of water flowing between the unsaturated zone and the aquifer. These fluxes, known as net recharge, are often used as the shared variable that couples unsaturated to groundwater models. However, as recharge estimates are always affected by a degree of uncertainty, model–data fusion methods, such as data assimilation, can be used to inform these coupled models and reduce uncertainty. This study assesses the effect of unsaturated zone models complexity (conceptual versus physically based) to update groundwater model outputs, through the assimilation of actual evapotranspiration rates, for a water-limited site in South Australia. Actual evapotranspiration rates are assimilated because they have been shown to be related to the water table dynamics and thus form the link between remote sensing data and the deeper parts of the soil profile. Results have been quantified using standard metrics, such as the root mean square error and Pearson correlation coefficient, and reinforced by calculating the continuous ranked probability score, which is specifically designed to determine a more representative error in stochastic models. It has been found that, once properly calibrated to reproduce the actual evapotranspiration–water table dynamics, a simple conceptual model may be sufficient for this purpose; thus using one configuration over the other should be motivated by the specific purpose of the simulation and the information available.

Water table dynamics are linked to the atmosphere through evapotranspiration and recharge. The assimilation of observed evapotranspiration values should thus improve groundwater model results. This paper presents a method for assimilating evapotranspiration data into a coupled unsaturated zone and groundwater model using the ensemble Kalman filter. The method is tested for a synthetically generated losing stream system in climatic conditions common in South Australia. The study focused on areas with a deep (recharge area) and a shallow (extraction area) water table and an intermediate area showing seasonal variations between these two (transition area). The data assimilation algorithm consistently improved the model states in the three areas when the ensemble spread was adequate. Improvements were also obtained in the calculation of net recharge and modeled actual evapotranspiration. The results indicate the potential to improve groundwater models using remote sensing observations of actual evapotranspiration values.

As the largest freshwater storage in the world, groundwater plays an important role in maintaining ecosystems and helping humans adapt to climate change. However, groundwater dynamics, such as groundwater recharge, cannot be measured directly and is influenced by spatially and temporally complex processes, models are therefore required to capture the dynamics and provide scientific advice for decision-making. This paper developed, estimated and compared the performance of linear regression, multi-layer perception (MLP) and Long Short-Term Memory (LSTM) models in predicting groundwater recharge. The experimental dataset consists of time series of annual recharge from the year 1970 to 2012, based on water table fluctuation estimates from 465 bores in the states of South Australia and Victoria, Australia. We identified the factors that influenced groundwater recharge and found that the correlation between rainfall and groundwater recharge was strongest. The linear regression model had the poorest fitting performance, with the root mean squared error (RMSE) being greater than 0.19 when various proportions of training data were considered. The MLP model outperformed the linear regression in the prediction capability, achieving RMSE = 0.11 when 80% of training data was considered. The LSTM model was found to have the best performance, whose root mean squared errors were less than 0.12 when various proportions of training data were applied. The relative importance of influential predictors was evaluated using the above three models.

The water table fluctuation method of estimating recharge is widely used because it is conceptually simple and easy to implement. The major source of uncertainty in the recharge estimates come from the specific yield. The apparent specific yield has a dependence on the depth to water table that makes its measurement difficult (if not impossible) for appropriate use in the water table fluctuation method. This study has treated the specific yield as a conceptual parameter that cannot be measured and has constrained it using a rejection sampling approach using probabilistic estimates of net recharge from the chloride mass balance method and excess water derived from the difference between precipitation and remotely sensed actual evapotranspiration. The method developed here provided probabilistic estimates of the ultimate specific yield and a probabilistic time series of gross recharge, both important in shallow water table environments. An additional benefit of the method is that by jointly constraining the three different recharge types (i.e., excess water, gross, and net recharge) they are assured of being internally consistent. The method was implemented for 58 bores across four catchments in Northern Australia that may see increased development in coming years.