Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

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Show simple item record Mockler, Eva M. Chun, K. P. Sapriza-Azuri, G. Bruen, Michael Wheater, H. S. 2016-11-16T17:03:48Z 2016-11-16T17:03:48Z 2016 the Authors en 2016-11
dc.identifier.citation Advances in Water Resources en
dc.description.abstract Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion. en
dc.language.iso en en
dc.publisher Elsevier en
dc.subject Uncertainty en
dc.subject Hydrological modelling en
dc.subject Rainfall modelling en
dc.subject Model parameters en
dc.subject Performance criteria en
dc.title Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations en
dc.type Journal Article en
dc.status Peer reviewed en
dc.identifier.volume 97 en
dc.identifier.startpage 299 en
dc.identifier.endpage 313 en
dc.identifier.doi 10.1016/j.advwatres.2016.10.008
dc.neeo.contributor Mockler|Eva M.|aut|
dc.neeo.contributor Chun|K. P.|aut|
dc.neeo.contributor Sapriza-Azuri|G.|aut|
dc.neeo.contributor Bruen|Michael|aut|
dc.neeo.contributor Wheater|H. S.|aut|
dc.description.othersponsorship Ireland Canada University Foundation (ICUF) en
dc.description.othersponsorship Irish Environmental Protection Agency en
dc.description.othersponsorship Global Institute for Water Security en
dc.internal.rmsid 668664302 2016-11-01T13:23:27Z

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