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Optimization of High-Resolution Monitoring of Nutrients and TOC in Karst Waters Using a Partial Least-Squares Regression Model of a UV–Visible Spectrometer

  • Aurélien ValletEmail author
  • Fanny Moiroux
  • Jean-Baptiste Charlier
Conference paper
Part of the Advances in Karst Science book series (AKS)

Abstract

For a cost-effective survey of water quality in aquifers with a fast chemical response, such as karst aquifers, continuous high-resolution monitoring by an automatic sensor is relevant. We tested the suitability of the s::can UV–visible spectrometer for continuous measuring in a karst environment of the parameters proposed by the probe manufacturer (NO3 and total organic carbon TOC) as well as other parameters, such as total phosphorus (TP). The spectrometer was installed at the Loue Spring (French Jura Mountains), where water was also sampled for chemical analysis of NO3, TOC, and TP at a frequency of 1 to 4 days. A calibration model was developed based on the partial least-squares regression (PLSR) method, applied to the absorption spectra. Our method showed good results. For NO3, both the factory calibration (\(R^{2} {_{\text{VAL}}} = 0.98\)) and our calibration model (\(R^{2} {_{\text{VAL}}} = 0.99\)) are very good. For TOC, except for a slight underestimation of some peaks, the low and high values are better reproduced by our model developed (\(R^{2} {_{\text{VAL}}} = 0.63\), or 0.23 with the factory calibration). For TP, despite a higher background noise, the overall dynamics are well simulated (\(R^{2} {_{\text{VAL}}} = 0.56\)). Finally, our results showed that processing the raw data of the spectrum measured by the spectrometer optimizes the high-frequency monitoring of water quality and provides a better prediction of some parameters, as well as giving promising results for the calibration of non-programmed parameters.

Keywords

Monitoring High-resolution Nutrients TOC Karst UV-Visible spectrometer Jura moutain 

Abbreviations

MSC

Multiple Scatter Correction

NCS

Non-Compensated Spectrum

PLSR

Partial Least-Square Regression

R2

Coefficient of determination

RMSE

Root-Mean-Square Error

TP

Total Phosphorus

TOC

Total Organic Carbon

1st Der.

First derivative of the raw spectra

Notes

Acknowledgements

The work was funded by the Rhone-Mediterranean and Corsica Water Agency, the Doubs Department, and the French Geological Survey (BRGM) under the QUARSTIC network project. The authors wish to thank the Syndicat Mixte de la Loue and notably Vanessa Stefani for assistance with the field work. We thank Philippe Marinot from s::can France for providing advice on the probe characteristics. The manuscript was improved by constructive comments from three anonymous reviewers.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Aurélien Vallet
    • 1
    Email author
  • Fanny Moiroux
    • 2
  • Jean-Baptiste Charlier
    • 2
  1. 1.BRGMDijonFrance
  2. 2.BRGM, Univ. MontpellierMontpellierFrance

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