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dc.contributor.authorBorgonovo, E.
dc.contributor.authorLu, X.
dc.contributor.authorPlischke, E.
dc.contributor.authorRakovec, O.
dc.contributor.authorHill, Mary C.
dc.date.accessioned2018-11-06T19:46:29Z
dc.date.available2018-11-06T19:46:29Z
dc.date.issued2017-08-21
dc.identifier.citationBorgonovo, E., X. Lu, E. Plischke, O. Rakovec, and M. C. Hill (2017), Making the most out of a hydrological model data set: Sensitivity analyses to open the model black-box, Water Resour. Res., 53, 7933–7950, doi:10.1002/2017WR020767.en_US
dc.identifier.urihttp://hdl.handle.net/1808/27231
dc.description.abstractIn this work, we investigate methods for gaining greater insight from hydrological model runs conducted for uncertainty quantification and model differentiation. We frame the sensitivity analysis questions in terms of the main purposes of sensitivity analysis: parameter prioritization, trend identification, and interaction quantification. For parameter prioritization, we consider variance‐based sensitivity measures, sensitivity indices based on the L1‐norm, the Kuiper metric, and the sensitivity indices of the DELSA methods. For trend identification, we investigate insights derived from graphing the one‐way ANOVA sensitivity functions, the recently introduced CUSUNORO plots, and derivative scatterplots. For interaction quantification, we consider information delivered by variance‐based sensitivity indices. We rely on the so‐called given‐data principle, in which results from a set of model runs are used to perform a defined set of analyses. One avoids using specific designs for each insight, thus controlling the computational burden. The methodology is applied to a hydrological model of a river in Belgium simulated using the well‐established Framework for Understanding Structural Errors (FUSE) on five alternative configurations. The findings show that the integration of the chosen methods provides insights unavailable in most other analyses.en_US
dc.publisherAmerican Geophysical Unionen_US
dc.rights© 2017. American Geophysical Union. All Rights Reserved.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.subjectSensitivity analysisen_US
dc.subjectModel parametersen_US
dc.subjectHydrological modelen_US
dc.subjectUncertaintyen_US
dc.titleMaking the most out of a hydrological model data set: Sensitivity analyses to open the model black‐boxen_US
dc.typeArticleen_US
kusw.kuauthorHill, Mary C.
kusw.kudepartmentGeologyen_US
dc.identifier.doihttps://doi.org/10.1002/2017WR020767en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-0545-3378
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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© 2017. American Geophysical Union. All Rights Reserved.
Except where otherwise noted, this item's license is described as: © 2017. American Geophysical Union. All Rights Reserved.