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Climate change affects natural systems, leading to increased acceleration of global water cycle and substantial impacts on the productivity of tropical rivers and the several ecosystem functions they provide. However, the anticipated impacts of climate change in terms of frequency and intensity of extreme events (e.g., droughts and floods) on hydrological systems across regions could be substantially different. This study therefore aims to assess the impacts of climate change on the streamflow of a large river basin located in central Australia (Cooper Creek-Bulloo River Basin). Modified version of the hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) was used in this study to generate daily streamflow. This model was first calibrated (2001–2010) and then validated for two independent periods (1993–1997 and 2011–2015). The model depicted a good performance in simulating observed streamflow. Climate projection data from multiple general circulation models (ACCESS1.0, CanESM2, CESM1-CAM5, CNRM-CM5, GFDL-ESM2M, HadGEM2-CC, MIROC5, NorESM1-M, ACCESS1-0, ACCESS1-3, CCSM4, CNRM-CM5, CSIRO-Mk3.6, GFDL-CM3, GFDL-ESM2M, HadGEM2, MIROC5, MPI-ESM-LR, and NorESM1-M) in various forms (raw, statistically downscaled, dynamically downscaled, and bias adjusted) were considered in this study. Results showed that three high resolution dynamically downscaled and bias adjusted models (ACCESS1-3, CNRM-CM5, and MPI-ESM-LR) from Terrestrial Ecosystem Research Network (TERN) dataset (v1.0.2) have better performance than other models considered, that is, in terms of capturing observed precipitation over the basin. Future climate projections of ensemble of these three models forced with RCP 4.5 and RCP 8.5 emission scenarios were then used to generate streamflow for 2050s (2040–2069) and 2080s (2070–2099). Results of the study indicated that mean annual precipitation was projected to decrease by up to −8% in 2050s and temperature was projected to increase by up to 4.66 °C in 2080s under the average and extreme emission scenarios, respectively. Mean annual, mean seasonal (December–February, March–May, June–August, September–November), and mean monthly streamflow were projected to decrease under different emission scenarios in 2050s and 2080s. These results indicate decreased water availability in the future as well as water cycle intensification. These changes in streamflow might have impacts on agriculture, natural ecosystem, and could lead to water restrictions. The outcome of this study can directly feed into frameworks for sustainable management of water resources and support adaptation strategies that rely on science and policy to improve water resources allocation in the region. [ABSTRACT FROM AUTHOR]

Abstract: Economic analysis of climate scenarios and alternative water policies is critical for development and implementation of appropriate water policies and programs. Mathematical models have been developed to assess water resources policies due to their ability to explicitly represent the biophysical dynamics of natural systems while integrating these within social and economic constraints. These models have been criticised, however, due to the problems of simplification, overspecialisation, plausibility and lack of empirical validation. This paper introduces a mathematical programming model which uses positive mathematical programming method to calibrate and model agriculture and water use in the Murray-Darling Basin of Australia. This paper reviews the theoretical and technical details of the model development including the key steps taken in collating and scaling the biophysical and economic data, and to address model parameterisation issues. The paper summarises results of an application of the model for assessing climate change impacts in the form of reduced rainfall and water allocations and increased crop water use for agricultural production. The results show the degree of variability in gross values under different climate scenarios compared to the base case scenario, especially in very dry years. The results also show how on-farm adaptation options and water markets can mitigate these losses. [Copyright &y& Elsevier]