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A regional neural network ensemble for predicting mean daily river water temperature

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Publication Date

Citation

Jefferson Tyrell DeWeber, and Tyler Wagner, 2014-09-19, A regional neural network ensemble for predicting mean daily river water temperature: Journal of Hydrology, v. 517, p. 187-200.

Summary

Abstract (from http://www.sciencedirect.com/science/article/pii/S0022169414003990#): Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May-October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used [...]

Contacts

Author :
Jefferson Tyrell DeWeber, Tyler Wagner
Funding Agency :
NCCWSC

Attached Files

Communities

  • National CASC
  • National and Regional Climate Adaptation Science Centers

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Citation Extension

citationTypeJournal Article
journalJournal of Hydrology
parts
typeVolume
value517
typePages
value187-200
typeDOI
value10.1016/j.jhydrol.2014.05.035

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