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| Titel |
TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks |
| VerfasserIn |
M. F. Müller, S. E. Thompson |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 6 ; Nr. 19, no. 6 (2015-06-24), S.2925-2942 |
| Datensatznummer |
250120751
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| Publikation (Nr.) |
 copernicus.org/hess-19-2925-2015.pdf |
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| Zusammenfassung |
| We introduce topological restricted maximum likelihood (TopREML) as
a method to predict runoff signatures in ungauged
basins. The approach is based on the use of linear mixed models with
spatially correlated random effects. The nested nature of streamflow networks
is taken into account by using water balance considerations to constrain the
covariance structure of runoff and to account for the stronger spatial
correlation between flow-connected basins. The restricted maximum likelihood
(REML) framework generates the best linear unbiased predictor (BLUP) of both
the predicted variable and the associated prediction uncertainty, even when
incorporating observable covariates into the model. The method was
successfully tested in cross-validation analyses on mean streamflow and
runoff frequency in Nepal (sparsely gauged) and Austria (densely gauged),
where it matched the performance of comparable methods in the prediction of
the considered runoff signature, while significantly outperforming them in
the prediction of the associated modeling uncertainty. The ability of TopREML to
combine deterministic and stochastic information to generate BLUPs of the
prediction variable and its uncertainty makes it a particularly versatile
method that can readily be applied in both densely gauged basins, where it
takes advantage of spatial covariance information, and data-scarce regions,
where it can rely on covariates, which are increasingly observable via remote-sensing technology. |
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