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Benchmarking seasonal forecasting skill using river flow persistence in Irish catchments

journal contribution
posted on 11.11.2020, 10:28 by Dáire Foran Quinn, Conor Murphy, Robert Wilby, Tom Matthews, Ciaran Broderick, Saeed Golian, Seán Donegan, Shaun Harrigan
This study assesses the seasonal forecast skill of river flow persistence in 46 catchments representing a range of hydrogeological conditions across Ireland. Skill is evaluated against a climatology benchmark forecast and by examining correlations between predicted and observed flow anomalies. Forecasts perform best when initialised in drier summer months, 87% of which show greater skill relative to the benchmark at a 1-month horizon. Such skill declines as forecast horizon increases due to the longer time a catchment has to “forget” initial anomalous flow conditions and/or to be impacted by “new” events. Skill is related to physical catchment descriptors such as the Baseflow Index (correlation ρ= 0.86) and is greatest in permeable high-storage catchments. The distinct seasonal and spatial variations in persistence skill allows us to pinpoint when and where this method can provide a useful benchmark in the future development of more complex seasonal hydrological forecasting approaches in Ireland.

Funding

Science Foundation Ireland Career Development Award (Grant No.: SFI/17/CDA/4783)

History

School

  • Social Sciences and Humanities

Department

  • Geography and Environment

Published in

Hydrological Sciences Journal

Publisher

Taylor & Francis

Version

AM (Accepted Manuscript)

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in Hydrological Sciences Journal on [date of publication], available online: http://www.tandfonline.com/[Article DOI].

Acceptance date

13/10/2020

ISSN

0262-6667

eISSN

2150-3435

Language

en

Depositor

Dr Tom Matthews. Deposit date: 9 November 2020

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