Fiber optics opens window on stream dynamics

John Selker; Nick C. van de Giesen; Martijn Westhoff; Wim Luxemburg; Marc B. Parlange

doi:10.1029/2006GL027979

Fiber optics opens window on stream dynamics

John Selker, Nick C. van de Giesen, Martijn Westhoff, Wim Luxemburg, Marc B. Parlange

Earth and Climate

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

A new approach to monitoring surface waters using distributed fiber optic temperature sensing is presented, allowing resolutions of temperature of 0.01Â°C every meter along a fiber optic cable of up to 10,000 m in length. We illustrate the potential of this approach by quantifying both stream temperature dynamics and groundwater inflows to the Maisbich, a first-order stream in Luxembourg (49Â°47艂N, 6Â°02艂E). The technique provides a very rich dataset, which may be of interest to many types of environmental research, notably that of stream ecosystems.

Original language	Undefined/Unknown
Pages (from-to)	L24401
Journal	Geophys. Res. Lett.
Volume	33
Issue number	24
DOIs	https://doi.org/10.1029/2006GL027979
Publication status	Published - 2006

Keywords

distributed temperature measurement streamflow groundwater 1830 Hydrology: Groundwater/surface water interaction 1848 Hydrology: Monitoring networks 1860 Hydrology: Streamflow 1871 Hydrology: Surface water quality 1878 Hydrology: Water/energy interactions

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1029/2006GL027979

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Cite this

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AU - van de Giesen, Nick C.

AU - Westhoff, Martijn

AU - Luxemburg, Wim

AU - Parlange, Marc B.

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AB - A new approach to monitoring surface waters using distributed fiber optic temperature sensing is presented, allowing resolutions of temperature of 0.01Â°C every meter along a fiber optic cable of up to 10,000 m in length. We illustrate the potential of this approach by quantifying both stream temperature dynamics and groundwater inflows to the Maisbich, a first-order stream in Luxembourg (49Â°47艂N, 6Â°02艂E). The technique provides a very rich dataset, which may be of interest to many types of environmental research, notably that of stream ecosystems.

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