Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/218478
COMPARTIR / EXPORTAR:
logo share SHARE logo core CORE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Título

Assessment of the Combined Effect of Temperature and Salinity on the Outputs of Soil Dielectric Sensors in Coconut Fiber

AutorBañón, Sebastián; Ochoa, J.; Bañón, Daniel; Ortuño Gallud, M. Fernanda CSIC ORCID; Sánchez-Blanco, María Jesús CSIC ORCID
Palabras claveSoil moisture
Probe
Salinity
Volumetric water content
Temperatures
Fecha de publicación2020
EditorMultidisciplinary Digital Publishing Institute
CitaciónSustainability 12(16): 6577 (2020)
ResumenDielectric sensors are useful instruments for measuring soil moisture and salinity. The soil moisture is determined by measuring the dielectric permittivity, while bulk electrical conductivity (EC) is measured directly. However, permittivity and bulk EC can be altered by many variables such as measurement frequency, soil texture, salinity, or temperature. Soil temperature variation is a crucial factor as there is much evidence showing that global warming is taking place. This work aims to assess how variations in the temperature and salinity of coconut fiber affect the output of EC5 (voltage) and GS3 (permittivity and bulk EC) Decagon sensors. The results showed that the effect of temperature and salinity on the output of the sensors can lead to substantial errors in moisture estimations. At low salinity values, permittivity readings decreased as temperature increased, while voltage readings were not affected, regardless of substrate moisture. The GS3 sensor underestimated the bulk EC when it is measured below 25 °C. The temperature dependence of the voltage of EC5 was not significant up to 10 dS m−1, and the permittivity of the GS3 was more affected by the interaction between temperature and salinity. The effect that salinity has on the permittivity of the GS3 sensor can be reduced if a permittivity–moisture calibration is performed with saline solutions, while the effect resulting from the interaction between temperature and salinity can be minimized using a regression model that considers such an interaction.
Versión del editorhttps://doi.org/10.3390/su12166577
URIhttp://hdl.handle.net/10261/218478
DOI10.3390/su12166577
E-ISSN2071-1050
Aparece en las colecciones: (CEBAS) Artículos




Ficheros en este ítem:
Fichero Descripción Tamaño Formato
Assessment_Bañon_Art2020.pdf1,74 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo

CORE Recommender

SCOPUSTM   
Citations

6
checked on 18-abr-2024

WEB OF SCIENCETM
Citations

5
checked on 17-feb-2024

Page view(s)

142
checked on 24-abr-2024

Download(s)

218
checked on 24-abr-2024

Google ScholarTM

Check

Altmetric

Altmetric


Este item está licenciado bajo una Licencia Creative Commons Creative Commons