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Profile photo of Ronny Berndtsson

Ronny Berndtsson

Professor, Dep Director, MECW Dep Scientific Coordinator

Profile photo of Ronny Berndtsson

Utilisation de réseaux de neurones pour l'étalonnage de mesures par réflectométrie en domaine temporel

Using neural networks for calibration of time-domain reflectometry measurements

Author

  • Magnus Persson
  • Ronny Berndtsson
  • Bellie Sivakumar

Summary, in English

Time-domain reflectometry (TDR) is an electromagnetic technique for measurements of water and solute transport in soils. The relationship between the TDR-measured dielectric constant (Ka) and bulk soil electrical conductivity ([sgrave]a) to water content (θW) and solute concentration is difficult to describe physically due to the complex dielectric response of wet soil. This has led to the development of mostly empirical calibration models. In the present study, artificial neural networks (ANNs) are utilized for calculations of θw and soil solution electrical conductivity ([sgrave]w) from TDR-measured Ka and [sgrave]a in sand. The ANN model performance is compared to other existing models. The results show that the ANN performs consistently better than all other models, suggesting the suitability of ANNs for accurate TDR calibrations.

Department/s

  • Division of Water Resources Engineering

Publishing year

2001

Language

French

Pages

389-398

Publication/Series

Hydrological Sciences Journal

Volume

46

Issue

3

Document type

Journal article

Publisher

Taylor & Francis

Topic

  • Oceanography, Hydrology, Water Resources

Keywords

  • Electrical conductivity
  • Neural networks
  • Soil water content
  • Time-domain reflectometry

Status

Published

ISBN/ISSN/Other

  • ISSN: 0262-6667