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Many studies bias correct daily precipitation from climate models to match the observed precipitation statistics, and the bias corrected data are then used for various modelling applications. This paper presents a review of recent methods used to bias correct precipitation from regional climate models (RCMs). The paper then assesses four bias correction methods applied to the weather research and forecasting (WRF) model simulated precipitation, and the follow-on impact on modelled runoff for eight catchments in southeast Australia. Overall, the best results are produced by either quantile mapping or a newly proposed two-state gamma distribution mapping method. However, the difference between the tested methods is small in the modelling experiments here (and as reported in the literature), mainly because of the substantial corrections required and inconsistent errors over time (non-stationarity). The errors remaining in bias corrected precipitation are typically amplified in modelled runoff. The tested methods cannot overcome limitation of RCM in simulating precipitation sequence, which affects runoff generation. Results further show that whereas bias correction does not seem to alter change signals in precipitation means, it can introduce additional uncertainty to change signals in high precipitation amounts and, consequently, in runoff. Future climate change impact studies need to take this into account when deciding whether to use raw or bias corrected RCM results. Nevertheless, RCMs will continue to improve and will become increasingly useful for hydrological applications as the bias in RCM simulations reduces. [ABSTRACT FROM AUTHOR]

This paper uses the Budyko and Fu models to estimate mean annual runoff in 0.05° grid cells across southeast Australia, and assesses the estimates against observations in 323 catchments. The results show that the Budyko model can provide reasonable estimates of runoff and is suitable for data limited regions. In regions where there are some streamflow data available, the calibration of a single parameter in the Fu model gives better runoff estimates than the Budyko model and similar to regionalised rainfall-runoff models. In drier regions, the consideration of different vegetation types in the Fu model can improve the modelling results. [ABSTRACT FROM AUTHOR]

Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large-scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south-east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI-ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO-MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS-AOM, MIROC-M, NCAR-PCM1, IAP and NCAR-CCSM. However, the reduction in the combined score as we move from the best- to the worst-performing GCMs is gradual, and there is no evident cut-off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study describes a daily rainfall, potential evaporation and streamflow data set compiled for the important water resources region of southeast Australia, and the application of six commonly used lumped conceptual rainfall-runoff models to estimate daily runoff across the region. The daily climate data set and the daily modelled runoff are available from 1895 to 2008 at 0.05° grid resolution across the region. The modelling exercise indicates that the rainfall-runoff models can generally be calibrated to reproduce the daily observed streamflow (for 232 catchments in the high runoff generation areas), and the regionalisation results indicate that the use of optimised parameter values from a gauged catchment nearby can model runoff reasonably well in the ungauged areas. There are differences between the six models, but they are relatively small when used to describe aggregated results across large regions. [ABSTRACT FROM AUTHOR]

Investigates the nutrient contribution from leaf litter in urban waterways. Nutrients in leaf litter; Variables from the 10 cleanouts of the continuous deflective separation (CDS) device; Management implications.