Abstract. A fully Bayesian approach to parameter estimation and inference in conceptual rainfall-runoff models (CRRMs) is presented. Computations are performed using a Markov chain Monte Carlo (MCMC) method based on the Metropolis-Hastings algorithm. Single-site and block updating schemes are used for model parameters subject to nonnegativity restrictions as well as interval, equality, and order constraints. Diagnostics for the convergence of the Markov chain and CRRM assessment are also considered. The MCMC approach produces samples from the joint posterior distribution of the model parameters. This provides more information than single-point estimates and avoids the need to use a normal approximation to the posterior as the basis for inference. The methodology is demonstrated using an eight-parameter conceptual rainfall-runoff model and two case studies from southeastern Australia. The first case study considers a watershed with high runoff yield over a 12-year period. The second case study considers a watershed with low yield over a 17,year period. The results indicate that (1) Bayesian methods provide an objective framework for model criticism and choice, (2) the proposed strategies for handling constraints on model parameters are effective, (3) the model parameters are sensitive to likelihood function selection, (4) the conventional approach of using a power transformation and an autoregressive process to stabilize error variance and model dependence in the residuals may have limited success, and (5) some care is required in the implementation of the MCMC approach and reliable results will be difficult to obtain when CRRM complexity exceeds the limitations of the rainfall-runoff data at hand. A key finding is that the MCMC scheme presented herein provides a powerful means of identifying specific inadequacies in the structure of CRRMs. IntroductionConceptual rainfall-runoff models (CRRMs) are a popular tool for simulating the land phase of the hydrologic cycle.

Since the mid-1970s the climatic changes that have taken place in southwest Western Australia have generated a variety of impacts, the most prominent of which is a reduction in dam inflows of at least 50 percent. These impacts were the catalyst for the formation of the Indian Ocean Climate Initiative in 1998, a research partnership between two national research organizations and several state government departments and agencies. This paper describes the key scientific findings of the Initiative with respect to the nature of the climatic changes that have taken place within the region, explores the factors that might have caused these changes, and describes the most recent climate projections for the region. We reflect on the factors leading to the rapid acceptance of the research outcomes from the Initiative, the impact of the Initiative on policy development across Australia and its likely evolution post-2006.

Abstract. Low-yielding catchments with ephemeral streams involve highly nonlinear relationships between rainfall and runoff, and there is much less documentation and appreciation of the ability to predict streamflow in these very difficult cases than in humid

Droughts have significant environmental and socio-economic impacts in Australia. This emphasizes Australia's vulnerability to climate variability and limitations of adaptive capacity. Two drought indices are compared for their potential utility in resource management. The Rainfall Deciles-based Drought Index is a measure of rainfall deficiency while the Soil-Moisture Deciles-based Drought Index is a measure of soil-moisture deficiency attributed to rainfall and potential evaporation. Both indices were used to assess future drought events over Australia under global warming attributed to low and high greenhouse gas emission scenarios (SRES B1 and A1F1 respectively) for 30-year periods centred on 2030 and 2070. Projected consequential changes in rainfall and potential evaporation were based on results from the CCCma1 and Mk2 climate models, developed by the Canadian Climate Center and the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) respectively. A general increase in drought frequency associated with global warming was demonstrated by both indices for both climate models, except for the western part of Australia. Increases in the frequency of soil-moisture-based droughts are greater than increases in meteorological drought frequency. By 2030, soil-moisture-based drought frequency increases 20-40% over most of Australia with respect to 1975-2004 and up to 80% over the Indian Ocean and southeast coast catchments by 2070. Such increases in drought frequency would have major implications for natural resource management, water security planning, water demand management strategies, and drought relief payments.