Journal
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
Volume 65, Issue 11, Pages 1856-1871Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2020.1764961
Keywords
distributed catchment-scale model; DiCaSM; GLUE; model uncertainty; River Eden; River Don; River Ebbw; River Frome; River Pang; UK
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Funding
- Natural Environment Research Council (NERC) [NE/L010292/1]
- NERC [NE/L01033X/1] Funding Source: UKRI
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In this study, the distributed catchment-scale model, DiCaSM, was applied on five catchments across the UK. Given its importance, river flow was selected to study the uncertainty in streamflow prediction using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology at different timescales (daily, monthly, seasonal and annual). The uncertainty analysis showed that the observed river flows were within the predicted bounds/envelope of 5% and 95% percentiles. These predicted river flow bounds contained most of the observed river flows, as expressed by the high containment ratio, CR. In addition to CR, other uncertainty indices - bandwidthB, relative bandwidth RB, degrees of asymmetrySandT, deviation amplitudeD, relative deviation amplitude RD and theRfactor - also indicated that the predicted river flows have acceptable uncertainty levels. The results show lower uncertainty in predicted river flows when increasing the timescale from daily to monthly to seasonal, with the lowest uncertainty associated with annual flows.
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