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HESS | Articles | Volume 22, issue 12
Hydrol. Earth Syst. Sci., 22, 6257–6278, 2018
https://doi.org/10.5194/hess-22-6257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 22, 6257–6278, 2018
https://doi.org/10.5194/hess-22-6257-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Dec 2018

Research article | 06 Dec 2018

Evaluating post-processing approaches for monthly and seasonal streamflow forecasts

Fitsum Woldemeskel et al.
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Cited articles  
Bennett, J. C., Wang, Q. J., Li, M., Robertson, D. E., and Schepen, A.: Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model, Water Resour. Res., 52, 8238–8259, https://doi.org/10.1002/2016WR019193, 2016. 
Bennett, J. C., Wang, Q. J., Robertson, D. E., Schepen, A., Li, M., and Michael, K.: Assessment of an ensemble seasonal streamflow forecasting system for Australia, Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, 2017. 
Bogner, K. and Kalas, M.: Error-correction methods and evaluation of an ensemble based hydrological forecasting system for the Upper Danube catchment, Atmos. Sci. Lett., 9, 95–102, https://doi.org/10.1002/asl.180, 2008. 
Bourdin, D. R., Nipen, T. N., and Stull, R. B.: Reliable probabilistic forecasts from an ensemble reservoir inflow forecasting system, Water Resour. Res., 50, 3108–3130, https://doi.org/10.1002/2014WR015462, 2014. 
Box, G. E. P. and Cox, D. R.: An analysis of transformations, J. R. Stat. Soc. Ser. B, 211–252, https://doi.org/10.2307/2287791, 1964. 
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This paper evaluates several schemes for post-processing monthly and seasonal streamflow forecasts using the Australian Bureau of Meteorology's streamflow forecasting system. Through evaluation across 300 catchments, the best-performing scheme has been identified, which is found to substantially improve important aspects of the forecast quality. This finding is significant because the improved forecasts help water managers and users of the service to make better-informed decisions.
This paper evaluates several schemes for post-processing monthly and seasonal streamflow...
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