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

Data sets

Supporting data for "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021) David McInerney, Mark Thyer, and Dmitri Kavetski

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.