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Assessment of a vertical high-resolution distributed-temperaturesensing system in a shallow thermohaline environment


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Created: Apr 01, 2018 at 6:42 p.m.
Last updated: Apr 09, 2018 at 6:14 p.m.
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Abstract

In shallow thermohaline-driven lakes it is important to measure temperature on fine spatial and temporal scales to detect stratification or different hydrodynamic regimes. Raman spectra distributed temperature sensing (DTS) is an approach available to provide high spatial and temporal temperature resolution. A vertical high-resolution DTS system was constructed to overcome the problems of typical methods used in the past, i.e., without disturbing the water column, and with resistance to corrosive environments. This paper describes a method to quantitatively assess accuracy, precision and other limitations of DTS systems tom fully utilize the capacity of this technology, with a focus on vertical high-resolution to measure temperatures in shallow thermohaline environments. It also presents a new method to manually calibrate temperatures along the optical fiber achieving significant improved resolution. The vertical highresolution DTS system is used to monitor the thermal behavior of a salt-gradient solar pond, which is an engineered shallow thermohaline system that allows collection and storage of solar energy for a long period of time. The vertical high-resolution DTS system monitors the temperature profile each 1.1 cm vertically and in time averages as small as 10 s. Temperature resolution as low as 0.035 ◦C is obtained when the data are collected at 5-min intervals.

Raw project data is available by contacting ctemps@unr.edu

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How to Cite

Suarez, F. (2018). Assessment of a vertical high-resolution distributed-temperaturesensing system in a shallow thermohaline environment, HydroShare, http://www.hydroshare.org/resource/19a15dd8f6094605a49060c1bf3734a4

This resource is shared under the Creative Commons Attribution CC BY.

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Comments

Samuel Pratt 5 years, 8 months ago

It is really important to measure temperature on fine spatial.
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Bryan Ruffin 5 years, 3 months ago

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