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Added value from 576 years of tree-ring records in the prediction of the Great Salt Lake level

Gillies, Robert R. ; Chung, Oi-Yu ; Simon Wang, S.-Y. ; DeRose, R. Justin ; Sun, Yan

Journal of hydrology (Amsterdam), 2015-10, Vol.529, p.962-968 [Periódico revisado por pares]

Elsevier B.V

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  • Título:
    Added value from 576 years of tree-ring records in the prediction of the Great Salt Lake level
  • Autor: Gillies, Robert R. ; Chung, Oi-Yu ; Simon Wang, S.-Y. ; DeRose, R. Justin ; Sun, Yan
  • Assuntos: Added value ; Climate ; Drought ; Elevation ; Fluctuation ; Forecast ; Freshwater ; Great Salt Lake ; Hydrology ; Mathematical models ; Salt lakes ; Terminals ; Tree-ring ; Water
  • É parte de: Journal of hydrology (Amsterdam), 2015-10, Vol.529, p.962-968
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: •We model the Great Salt Lake level using 576years of tree-ring data.•The tree-ring reconstruction of lake level captures multidecadal cycles.•The forecast that combines the tree-ring data outperformed those that do not.•We produce a 5-year prediction that can assist in practical risk management. Predicting lake level fluctuations of the Great Salt Lake (GSL) in Utah – the largest terminal salt-water lake in the Western Hemisphere – is critical from many perspectives. The GSL integrates both climate and hydrological variations within the region and is particularly sensitive to low-frequency climate cycles. Since most hydroclimate variable records cover less than a century, forecasting the predominant yet under-represented decadal variability of the GSL level with such relatively short instrumental records poses a challenge. To overcome data limitations, this study assesses two options: (1) developing a model using the observational GSL elevation record of 137years to predict itself; (2) incorporating the recently reconstructed GSL elevation that utilized 576years worth of tree-ring records into the predictive model. It was found that the statistical models that combined the tree-ring reconstructed data with the observed data outperformed those that did not, in terms of reducing the root mean squared errors. Such predictive models can serve as a means toward practical water risk management.
  • Editor: Elsevier B.V
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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