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Benchmarking seasonal forecasting skill using river flow persistence in Irish catchments
journal contributionposted 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.
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Science Foundation Ireland Career Development Award (Grant No.: SFI/17/CDA/4783)
- Social Sciences and Humanities
- Geography and Environment