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Evaluation of modified Hilhorst models for pore electrical conductivity estimation using a low‑cost dielectric sensor

Zemni, Nessrine LU ; Bouksila, Fethi LU ; Slama, Fairouz ; Persson, Magnus LU ; Berndtsson, Ronny LU orcid and Bouhlila, Rachida (2022) In Arabian Journal of Geosciences 15(11). p.1-9
Abstract (Swedish)
Real-time measurement of soil water content (θ) and pore electrical conductivity (ECp) is essential to improve water irriga-tion efficiency and agricultural productivity. Low-cost frequency domain reflectometry (FDR) sensors are now representinga powerful tool for irrigation management purposes. However, compared to the time domain reflectometry (TDR), FDRsensors’ accuracy to predict θ and ECp is negatively affected by saline conditions. Thus, it is necessary to determine the soilsalinity range where FDR probes are not recommended in precise irrigated agriculture and to select the appropriate modelsfor ECp estimation especially under saline conditions. Low-cost sensors, however, often use the default Hilhorst model forECp determination,... (More)
Real-time measurement of soil water content (θ) and pore electrical conductivity (ECp) is essential to improve water irriga-tion efficiency and agricultural productivity. Low-cost frequency domain reflectometry (FDR) sensors are now representinga powerful tool for irrigation management purposes. However, compared to the time domain reflectometry (TDR), FDRsensors’ accuracy to predict θ and ECp is negatively affected by saline conditions. Thus, it is necessary to determine the soilsalinity range where FDR probes are not recommended in precise irrigated agriculture and to select the appropriate modelsfor ECp estimation especially under saline conditions. Low-cost sensors, however, often use the default Hilhorst model forECp determination, and in salty soils, this use is not correct. Thus, we present a new and improved Hilhorst model of ECpestimation. We also assess the performance of the low-cost Water, Electrical conductivity, and Temperature (WET) sen-sor and to test the new ECp model under saline conditions. Consequently, the ECp was predicted using, first, a polynomialmodel in which ECa effect on the soil parameter K0 is considered and second, a linear model in which the ECa effect on soilapparent dielectric permittivity Ka is considered. The performance of the proposed models is evaluated by measurements ofthe WET sensor in sandy porous media collected in the Tunisian Jemna oasis using seven different levels of NaCl solutions(0.02 to 8.2 dSm−1) and compared to TDR measurements. Results show that using the default Hilhorst model, the root meansquare error (RMSE) of ECp predictions was higher than 0.5 dSm−1 using WET sensor. However, if considering the bulkelectrical conductivity (ECa) effect on the soil parameter K0 instead of using the standard values in the Hilhorst model, theperformance of the WET sensor to predict ECp increased with a mean RMSE equal to 0.1 dSm−1.

(1) (PDF) Evaluation of modified Hilhorst models for pore electrical conductivity estimation using a low-cost dielectric sensor. Available from: https://www.researchgate.net/publication/361016731_Evaluation_of_modified_Hilhorst_models_for_pore_electrical_conductivity_estimation_using_a_low-cost_dielectric_sensor [accessed Oct 02 2023]. (Less)
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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Arabian Journal of Geosciences
volume
15
issue
11
pages
9 pages
publisher
Springer
ISSN
1866-7511
DOI
10.1007/s12517-022-10354-5
language
English
LU publication?
yes
id
3559b09d-c892-4c87-b843-bc434f282229
date added to LUP
2023-10-02 15:27:14
date last changed
2023-11-13 09:10:05
@article{3559b09d-c892-4c87-b843-bc434f282229,
  abstract     = {{Real-time measurement of soil water content (θ) and pore electrical conductivity (ECp) is essential to improve water irriga-tion efficiency and agricultural productivity. Low-cost frequency domain reflectometry (FDR) sensors are now representinga powerful tool for irrigation management purposes. However, compared to the time domain reflectometry (TDR), FDRsensors’ accuracy to predict θ and ECp is negatively affected by saline conditions. Thus, it is necessary to determine the soilsalinity range where FDR probes are not recommended in precise irrigated agriculture and to select the appropriate modelsfor ECp estimation especially under saline conditions. Low-cost sensors, however, often use the default Hilhorst model forECp determination, and in salty soils, this use is not correct. Thus, we present a new and improved Hilhorst model of ECpestimation. We also assess the performance of the low-cost Water, Electrical conductivity, and Temperature (WET) sen-sor and to test the new ECp model under saline conditions. Consequently, the ECp was predicted using, first, a polynomialmodel in which ECa effect on the soil parameter K0 is considered and second, a linear model in which the ECa effect on soilapparent dielectric permittivity Ka is considered. The performance of the proposed models is evaluated by measurements ofthe WET sensor in sandy porous media collected in the Tunisian Jemna oasis using seven different levels of NaCl solutions(0.02 to 8.2 dSm−1) and compared to TDR measurements. Results show that using the default Hilhorst model, the root meansquare error (RMSE) of ECp predictions was higher than 0.5 dSm−1 using WET sensor. However, if considering the bulkelectrical conductivity (ECa) effect on the soil parameter K0 instead of using the standard values in the Hilhorst model, theperformance of the WET sensor to predict ECp increased with a mean RMSE equal to 0.1 dSm−1. <br/><br/>(1) (PDF) Evaluation of modified Hilhorst models for pore electrical conductivity estimation using a low-cost dielectric sensor. Available from: https://www.researchgate.net/publication/361016731_Evaluation_of_modified_Hilhorst_models_for_pore_electrical_conductivity_estimation_using_a_low-cost_dielectric_sensor [accessed Oct 02 2023].}},
  author       = {{Zemni, Nessrine and Bouksila, Fethi and Slama, Fairouz and Persson, Magnus and Berndtsson, Ronny and Bouhlila, Rachida}},
  issn         = {{1866-7511}},
  language     = {{eng}},
  month        = {{03}},
  number       = {{11}},
  pages        = {{1--9}},
  publisher    = {{Springer}},
  series       = {{Arabian Journal of Geosciences}},
  title        = {{Evaluation of modified Hilhorst models for pore electrical conductivity estimation using a low‑cost dielectric sensor}},
  url          = {{http://dx.doi.org/10.1007/s12517-022-10354-5}},
  doi          = {{10.1007/s12517-022-10354-5}},
  volume       = {{15}},
  year         = {{2022}},
}