During the Millennium Drought in southeast Australia (2001-2009), dryland wetlands experienced widespread ecological deterioration, which highlighted their vulnerability to natural climate variability and the potential effects of drying climate change. Here we use 30-year observed streamflow data (1991-2020) and numerical models to assess the impacts of climate variability and climate change on the Macquarie Marshes (the Marshes), a large floodplain wetland complex in the semi-arid region of New South Wales, Australia. A fast ecohydrologic emulator based on network linear programming with side constraints was developed to simulate the spatial and temporal responses of different wetland vegetation types to water regime. The emulator represents the wetland by a series of inter-connected level-pool reservoirs with the volume-discharge relationship obtained from a calibrated quasi-2d hydrodynamic model. The emulator reproduces daily flows and volume with good accuracy (Nash-Sutcliffe statistic ranging from 0.61 to 0.96) with 1/26,000 of the computational effort. We use the emulator to simulate the potential effects of climatic variability on vegetation by running the model over 30 years of observed data and 1000 statistically representative 30-year streamflow time series, which were generated using a stochastic model calibrated to the gauged flows. The collection of results for all 1000 contemporary simulations indicates the Marshes experience severe conditions 43% (± 18%) of the time in a 30-year period. We then ran an additional 6000 simulations to assess the combined impacts of climate variability and future climate change at the end of the century. For the driest future climates (-60% and -30% reduction in runoff), the Marshes remain in severe condition 89% (± 6%) and 63% (± 16%) of the time, respectively, while no major differences with respect to the contemporary conditions were found for the wetter future. Our results highlight the importance of quantifying the extent and uncertainty in the degradation of these ecosystems due to climate variability and change for informing management decisions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)