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This paper describes an approach to estimate drought severity for drought response planning and urban water management considering the impacts of climate change and variability. Low flow frequency analysis was used to estimate drought severity (eg. 1-in-100-year average recurrence interval) of different drought durations from several months to years. Traditionally this was done using available historical streamflow record. However, recent research including the South Eastern Australian Climate Initiative has indicated that the prolonged drought experienced in southeastern Australia including Melbourne in the recent decade since 1997 has been unprecedented in historical context, and is potentially part of a long-term trend associated with global warming. This raises the issue of the practicality of the assumption of hydrologic stationarity. To account for the potential for more severe and frequent drought events, an adaptive approach is needed to adapt to the drier future in a changing and variable climate by considering experience from the recent 1997-2009 drought and the latest climate change projections. In this paper, drought severity for the Melbourne system is estimated based on historical streamflow data with monthly flow prior to 1997 adjusted using a flow duration curve decile method to reflect the recent dry conditions of 1997-2009. The approach is consistent with recommendations in the Victorian Guidelines for the Development of a Water Supply-Demand Strategy (DSE, 2011). The results indicate that drought severity and frequency increased by an order of magnitude under a changed climate based on a "return to dry" scenario. This shift in severity and frequency highlights the need for adaptive planning methods to address changes in hydrologic conditions under a variable and changing climate. However, it also raises many challenges for drought planning including uncertainties in climate change projections, attribution of recent drought to climate change and variability, and the appropriate hydro-climate baseline for applying climate change projections. [ABSTRACT FROM AUTHOR]

The energy sector is undergoing major transformation. An under-recognised aspect of this transformation is the implications it has for the availability and quality of our freshwater water resources. Indeed, population growth combined with climate change and associated policies to address it, pose significant challenges for how we use our precious water resources, and the energy sector is set to become an increasingly important "user" of water in the decades to come. However, despite the important links, and parallels, between the two sectors, the two commodities are perceived, governed and managed in markedly different ways. This paper explores four aspects of the energy sector's transformation that pose particular challenges for water governance. [ABSTRACT FROM AUTHOR]

Projections of future water availability are required by water managers and policy makers in order to take action to mitigate some of the potentially negative impacts of climate change on water supplies in the urban, agricultural and environmental sectors. However, in order to do this, these projections must have some level of confidence associated with them, and even if this is the case, the research community must make the data and/or information available in a format that is directly usable by water managers and policy makers. This paper presents results from a water availability study recently carried out across southeastern Australia as part of the South Eastern Australian Climate Initiative. More importantly, it shows how the results of this study have been used in defining a range of plausible future streamflow scenarios to be used by water resource managers in the state of Victoria in updating its water supply-demand strategies for the next 50 years. Climate change projections for this region were summarised by creating "dry", "wet" and "median" future runoff scenarios for 2030 and 2060 based on the second driest, second wettest and median global climate model (GCM) results. These results were then averaged across 27 catchments covering the state of Victoria. We contend that in areas such as the state of Victoria where there is near-unanimous agreement among GCMs as to the direction of climate change impacts on rainfall, along with theoretical understanding consistent with changes in large scale circulation in a warmer world, projected changes in water availability can be used by water resource planners to assist them in better planning for future changes in supply. [ABSTRACT FROM AUTHOR]

Water and climate are two of the most important public policy challenges facing Australia. They have pervasive impacts on how and where people can live and what they are likely to be able to do in the future. Policy implementation in these areas suffers from a range of challenges, including how to improve horizon scanning and preparedness, learn from past policy experiences, deal with policy interdependencies, and develop forms of more citizen-centric policy. When these challenges are responded to effectively, it can lead to enhanced foresight and planning, better understanding and communication of policy complexity, and communication of uncertainty and ambiguity, that are key to effective policy implementation. In this context, this paper presents and analyses a number of practical responses to water and climate policy implementation challenges, including the development of "low regret" policy and infrastructure options that encourage flexibility in responding to possible futures. It also highlights the important role that collaboratively acting now across sectors, issues, governance levels and groups of stakeholders to plan for a range of future scenarios can have on enhancing the capacity of all involved and building pathways to more sustainable and resilient futures. [ABSTRACT FROM AUTHOR]

Predictions of rainfall spatial and temporal variability (including climate change effects) on a catchment basis are urgently required by water resource planners within Australia. Large spatial scale predictions of (typically 300 to 500 km grids) global scale climate scenarios output by General Circulation Models (GCMs) are inadequate for such use as they do not capture the large degree of spatial variability over smaller distances, which is inherent in rainfall. Multisite daily rainfall - a common requirement within many hydrological models - is a required input for modelling complex multi-catchment systems, as small scale spatial variability due to factors such as topography has a large bearing on how much rainfall falls in a given area. Statistical downscaling is a technique that can produce such fi ne spatial scale rainfall pattern predictions conditional on the larger scale climate scenarios output by a GCM. The GLIMCLIM (Generalised Linear Model for daily Climate time series) software package (Chandler, 2002) has been used to analyse and simulate spatial daily rainfall given natural climate variability infl uences in the UK, and further to predict the infl uence of various future climate scenarios on regional rainfall by downscaling larger spatial scale GCM simulations. This paper describes the comparison of this method to the non-parametric, non-homogeneous hidden Markov model - kernel probability density estimation (NNHMM-KDE) downscaling technique of Mehrotra & Sharma (2006), a method which has found application in Australia previously. [ABSTRACT FROM AUTHOR]