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A statistical method to predict flow permanence in dryland streams from time series of stream temperature

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Arismendi, I., Dunham, J.B., Heck, M.P., Schultz, L.D., Hockman-Wert, D.P., 2017, A statistical method to predict flow permanence in dryland streams from time series of stream temperature: Water, v. 9, no. 12, p. 946, https://doi.org/10.3390/w9120946.

Summary

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose [...]

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Type Scheme Key
local-index unknown 70195325
local-pk unknown 70195325
doi http://www.loc.gov/standards/mods/mods-outline-3-5.html#identifier doi:10.3390/w9120946
series unknown Water

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journalWater
parts
typevolume
value9
typeissue
value12
languageEnglish
citationTypeArticle

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