IDEAS home Printed from https://ideas.repec.org/a/caa/jnlswr/v15y2020i2id227-2018-swr.html
   My bibliography  Save this article

The laboratory calibration of a soil moisture capacitance probe in sandy soils

Author

Listed:
  • Marina Campora

    (Genoa, Italy)

  • Anna Palla

    (Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy)

  • Ilaria Gnecco

    (Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy)

  • Rossella Bovolenta

    (Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy)

  • Roberto Passalacqua

    (Department of Civil, Chemical and Environmental Engineering, University of Genoa, Genoa, Italy)

Abstract

Determining and mitigating landslide risk is a technical-scientific objective, particularly for the protection and proper territorial management and planning. The slope stability depends on the pore pressure distribution, which is influenced by the saturation front propagation through the unsaturated zone, whose monitoring is useful to understand any possible instabilities. Such monitoring may be undertaken by sensors based on the measurement of the relative dielectric permittivity. Reliable relationships between the measurement and the soil moisture are necessary. The main objective of this study is to assess a laboratory calibration protocol for a specific capacitance sensor (Drill & Drop, Sentek Sensor Technologies). Two monogranular sands have been selected for the calibration purpose. The laboratory tests were performed under three relative density values (DR equal to 40%, 60% and 80%) for seven volumetric water content values (θv ranging from 0.00% to 36.26%). Based on the experimental measurements, the soil-specific calibration curves were determined at an assigned relative density value; in particular, a simple power law is adopted to describe the probe's reading as a function of the volumetric water content. The results point out that the relative density values slightly affect the tests, thus, the soil-specific calibration curves are derived based on a simple regression analysis fitting the whole set of the laboratory tests validated for each sand. The calculated coefficient of determination (R2 = 0.96/0.99) and root mean square error (RMSE = 1.4%/2.8%) values confirm the goodness of fit. In order to propose more general fitting curves, suitable for both the investigated sands, multiple linear regressions are performed by considering θv and the mean grain size, D50 as independent variables; again, the R2 and RMSE values equal to 0.97 and 2.41%, respectively, confirm the suitability of the calibration curve. Finally, the laboratory calibration curves are compared with the manufacturer-supplied curves, thus, enhancing the need for the soil-specific calibration.

Suggested Citation

  • Marina Campora & Anna Palla & Ilaria Gnecco & Rossella Bovolenta & Roberto Passalacqua, 2020. "The laboratory calibration of a soil moisture capacitance probe in sandy soils," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 15(2), pages 75-84.
  • Handle: RePEc:caa:jnlswr:v:15:y:2020:i:2:id:227-2018-swr
    DOI: 10.17221/227/2018-SWR
    as

    Download full text from publisher

    File URL: http://swr.agriculturejournals.cz/doi/10.17221/227/2018-SWR.html
    Download Restriction: free of charge

    File URL: http://swr.agriculturejournals.cz/doi/10.17221/227/2018-SWR.pdf
    Download Restriction: free of charge

    File URL: https://libkey.io/10.17221/227/2018-SWR?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. De Caro, Dario & Ippolito, Matteo & Cannarozzo, Marcella & Provenzano, Giuseppe & Ciraolo, Giuseppe, 2023. "Assessing the performance of the Gaussian Process Regression algorithm to fill gaps in the time-series of daily actual evapotranspiration of different crops in temperate and continental zones using gr," Agricultural Water Management, Elsevier, vol. 290(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:caa:jnlswr:v:15:y:2020:i:2:id:227-2018-swr. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ivo Andrle (email available below). General contact details of provider: https://www.cazv.cz/en/home/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.