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| Titel |
Using multi-model averaging to improve the reliability of catchment scale nitrogen predictions |
| VerfasserIn |
J.-F. Exbrayat, N. R. Viney, H.-G. Frede, L. Breuer |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 6, no. 1 ; Nr. 6, no. 1 (2013-01-29), S.117-125 |
| Datensatznummer |
250017362
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| Publikation (Nr.) |
 copernicus.org/gmd-6-117-2013.pdf |
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| Zusammenfassung |
| Hydro-biogeochemical models are used to foresee the impact of mitigation
measures on water quality. Usually, scenario-based studies rely on single
model applications. This is done in spite of the widely acknowledged
advantage of ensemble approaches to cope with structural model uncertainty
issues. As an attempt to demonstrate the reliability of such multi-model
efforts in the hydro-biogeochemical context, this methodological
contribution proposes an adaptation of the reliability ensemble averaging
(REA) philosophy to nitrogen losses predictions. A total of 4 models are
used to predict the total nitrogen (TN) losses from the well-monitored Ellen
Brook catchment in Western Australia. Simulations include re-predictions of
current conditions and a set of straightforward management changes targeting
fertilisation scenarios. Results show that, in spite of good calibration
metrics, one of the models provides a very different response to management
changes. This behaviour leads the simple average of the ensemble members to
also predict reductions in TN export that are not in agreement with the
other models. However, considering the convergence of model predictions in
the more sophisticated REA approach assigns more weight to previously less
well-calibrated models that are more in agreement with each other. This
method also avoids having to disqualify any of the ensemble members. |
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