Articles | Volume 26, issue 21
Research article
10 Nov 2022
Research article |  | 10 Nov 2022

Seamless streamflow forecasting at daily to monthly scales: MuTHRE lets you have your cake and eat it too

David McInerney, Mark Thyer, Dmitri Kavetski, Richard Laugesen, Fitsum Woldemeskel, Narendra Tuteja, and George Kuczera

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Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts
Richard Laugesen, Mark Thyer, David McInerney, and Dmitri Kavetski
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Evaluating post-processing approaches for monthly and seasonal streamflow forecasts
Fitsum Woldemeskel, David McInerney, Julien Lerat, Mark Thyer, Dmitri Kavetski, Daehyok Shin, Narendra Tuteja, and George Kuczera
Hydrol. Earth Syst. Sci., 22, 6257–6278,,, 2018
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State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application
Matthew S. Gibbs, David McInerney, Greer Humphrey, Mark A. Thyer, Holger R. Maier, Graeme C. Dandy, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 22, 871–887,,, 2018
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Estimating changes in temperature extremes from millennial-scale climate simulations using generalized extreme value (GEV) distributions
Whitney K. Huang, Michael L. Stein, David J. McInerney, Shanshan Sun, and Elisabeth J. Moyer
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Cited articles

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Bureau of Meteorology: Long-range weather, climate and hydrology,
Short summary
Streamflow forecasts a day to a month ahead are highly valuable for water resources management. Current practice often develops forecasts for specific lead times and aggregation timescales. In contrast, a single, seamless forecast can serve multiple lead times/timescales. This study shows seamless forecasts can match the performance of forecasts developed specifically at the monthly scale, while maintaining quality at other lead times. Hence, users need not sacrifice capability for performance.