TY - JOUR
T1 - DTSGUI: A Python Program to Process and Visualize Fiber-Optic Distributed Temperature Sensing Data
AU - Domanski, Marian
AU - Quinn, Daven
AU - Day-Lewis, Frederick D.
AU - Briggs, Martin A.
AU - Werkema, Dale
AU - Lane, John W.
N1 - Funding Information:
This work was funded by the USGS Water Availability and Use Science Program (WAUSP). The U.S. Environmental Protection Agency partially funded and collaborated in the research described in the Example section under contract EP10D000782 through its Office of Research and Development. The authors gratefully acknowledge review comments from Andrew Leaf (USGS), Grant Ferguson, and Scott Tyler. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Funding Information:
This work was funded by the USGS Water Availability and Use Science Program (WAUSP). The U.S. Environmental Protection Agency partially funded and collaborated in the research described in the Example section under contract EP10D000782 through its Office of Research and Development. The authors gratefully acknowledge review comments from Andrew Leaf (USGS), Grant Ferguson, and Scott Tyler. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
Publisher Copyright:
© 2019, National Ground Water Association.
PY - 2020/9
Y1 - 2020/9
N2 - Fiber-optic distributed temperature sensing (FO-DTS) has proven to be a transformative technology for the hydrologic sciences, with application to diverse problems including hyporheic exchange, groundwater/surface-water interaction, fractured-rock characterization, and cold regions hydrology. FO-DTS produces large, complex, and information-rich datasets. Despite the potential of FO-DTS, adoption of the technology has been impeded by lack of tools for data processing, analysis, and visualization. New tools are needed to efficiently and fully capitalize on the information content of FO-DTS datasets. To this end, we present DTSGUI, a public-domain Python-based software package for editing, parsing, processing, statistical analysis, georeferencing, and visualization of FO-DTS data.
AB - Fiber-optic distributed temperature sensing (FO-DTS) has proven to be a transformative technology for the hydrologic sciences, with application to diverse problems including hyporheic exchange, groundwater/surface-water interaction, fractured-rock characterization, and cold regions hydrology. FO-DTS produces large, complex, and information-rich datasets. Despite the potential of FO-DTS, adoption of the technology has been impeded by lack of tools for data processing, analysis, and visualization. New tools are needed to efficiently and fully capitalize on the information content of FO-DTS datasets. To this end, we present DTSGUI, a public-domain Python-based software package for editing, parsing, processing, statistical analysis, georeferencing, and visualization of FO-DTS data.
UR - http://www.scopus.com/inward/record.url?scp=85078292225&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078292225&partnerID=8YFLogxK
U2 - 10.1111/gwat.12974
DO - 10.1111/gwat.12974
M3 - Article
C2 - 31840251
AN - SCOPUS:85078292225
SN - 0017-467X
VL - 58
SP - 799
EP - 804
JO - GroundWater
JF - GroundWater
IS - 5
ER -