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Paired Air and Stream Temperature Analysis (PASTA) to Evaluate Groundwater Influence on Streams

Hare, Danielle K.; Benz, Susanne A. ORCID iD icon 1; Kurylyk, Barret L.; Johnson, Zachary C.; Terry, Neil C.; Helton, Ashley M.
1 Institut für Photogrammetrie und Fernerkundung (IPF), Karlsruher Institut für Technologie (KIT)

Abstract:

Groundwater is critical for maintaining stream baseflow and thermal stability; however, the influence of groundwater on streamflow has been difficult to evaluate at broad spatial scales. Techniques such as baseflow separation necessitate streamflow records and do not directly indicate whether groundwater inflow may be sourced from more dynamic shallow flowpaths. We present a web tool application PASTA (Paired Air and Stream Temperature Analysis; https://cuahsi.shinyapps.io/pasta/) that capitalizes on increased public stream temperature data availability and large-scale, gridded climate observations to provide new and efficient insights regarding relative groundwater influence on streams. PASTA analyzes paired air and stream water temperature signals to evaluate spatiotemporal patterns in stream thermal sensitivity and relative groundwater influence, including inference regarding the dominant source groundwater depth (shallow or deep (i.e., approximately >6 m depth)). The tool is linked to publicly available stream temperature datasets and accepts user-uploaded datasets. As local air temperature is not often monitored, PASTA pulls daily air temperature data from the comprehensive Daymet products when directly measured data are unavailable, allowing the repurposing of existing stream temperature data. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000158604
Veröffentlicht am 12.10.2023
Originalveröffentlichung
DOI: 10.1029/2022WR033912
Scopus
Zitationen: 4
Web of Science
Zitationen: 5
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 04.2023
Sprache Englisch
Identifikator ISSN: 0043-1397, 1944-7973
KITopen-ID: 1000158604
HGF-Programm 12.11.31 (POF IV, LK 01) New observational systems and cross platform integration
Erschienen in Water Resources Research
Verlag John Wiley and Sons
Band 59
Heft 4
Seiten e2022WR033912
Vorab online veröffentlicht am 11.04.2023
Nachgewiesen in Web of Science
Dimensions
Scopus
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