Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Feb 10;22(4):1365.
doi: 10.3390/s22041365.

Soil Water Content Prediction Using Electrical Resistivity Tomography (ERT) in Mediterranean Tree Orchard Soils

José A Acosta  1 , María Gabarrón  1 , Marcos Martínez-Segura  2 , Silvia Martínez-Martínez  1 , Ángel Faz  1 , Alejandro Pérez-Pastor  1 , María Dolores Gómez-López  1 , Raúl Zornoza  1
Affiliations

Soil Water Content Prediction Using Electrical Resistivity Tomography (ERT) in Mediterranean Tree Orchard Soils

José A Acosta et al. Sensors (Basel). .

Abstract

Water scarcity in arid and semiarid regions poses problems for agricultural systems, awakening special interest in the development of deficit irrigation strategies to improve water conservation. Toward this purpose, farmers and technicians must monitor soil water and soluble nutrient contents in real time using simple, rapid and economical techniques through time and space. Thus, this study aimed to achieve the following: (i) create a model that predicts water and soluble nutrient contents in soil profiles using electrical resistivity tomography (ERT); and (ii) apply the model to different woody crops under different irrigation regimes (full irrigation and regulated deficit irrigation (RDI)) to assess the efficiency of the model. Simple nonlinear regression analysis was carried out on water content and on different ion contents using electrical resistivity data as the dependent variable. A predictive model for soil water content was calibrated and validated with the datasets based on exponential decay of a three-parameter equation. Nonetheless, no accurate model was achieved to predict any soluble nutrient. Electrical resistivity images were replaced by soil water images after application of the predictive model for all studied crops. They showed that under RDI situations, soil profiles became drier at depth while plant roots seemed to uptake more water, contributing to reductions in soil water content by the creation of desiccation bulbs. Therefore, the use of ERT combined with application of the validated predictive model could be a sustainable strategy to monitor soil water evolution in soil profiles under irrigated fields, facilitating land irrigation management.

Keywords: electrical resistivity; nonlinear regression analysis; regulated deficit irrigation; soil moisture; tomography.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Locations of the selected orchards.
Figure 2
Figure 2
Scheme of the methodology applied in our study.
Figure 3
Figure 3
Arrangement of electrodes for a 2D electrical survey and pseudosection data patterns for the Wenner–Schlumberger arrays.
Figure 4
Figure 4
Calibrated model (exponential decay of a three-parameter equation) for soil moisture estimation using the logarithm of electrical resistivity as the explanatory variable (n = 53).
Figure 5
Figure 5
Relationship between real moisture and calculated moisture using the calibrated model (CI-U: upper limit of the confidence interval; CI-L: lower limit of the confidence level).
Figure 6
Figure 6
Resistivity model (top) and predicted soil moisture (bottom) for control (left) and deficit irrigation (right) in the peach orchard.
Figure 7
Figure 7
Resistivity model (top) and predicted soil moisture (bottom) for control (left) and deficit irrigation (right) in the nectarine orchard.
Figure 8
Figure 8
Resistivity model (top) and predicted soil moisture (bottom) for control (left) and deficit irrigation (right) in the Saturn peach orchard.
Figure 9
Figure 9
Resistivity model (top) and predicted soil moisture (bottom) for control (left) and deficit irrigation (right) in the table grape orchard.
See this image and copyright information in PMC

References

    1. MAEC . Desertificación. Ministerio de Asuntos Exteriores. MAEC; Madrid, Spain: 2018.
    1. Tomás M., Medrano H., Escalona J.M., Martorell S., Pou A., Ribas-Carbó M., Flexas J. Variability of water use efficiency in grapevines. Environ. Exp. Bot. 2014;103:148–157. doi: 10.1016/j.envexpbot.2013.09.003. - DOI
    1. Hydrological Plan of the Segura River Basin . Memoria PHDS 2015/21. Confederación Hidrográfica del Segura, Ministerio de Agricultura, Alimentación y Medio Ambiente. Spanish Government; Madrid, Spain: 2015. p. 806.
    1. Bastida F., Torres I.F., Romero-Trigueros C., Baldrian P., Vetrovsky T., Bayona J.M., Alarcon J.J., Hernandez T., Garcia C., Nicolas E. Combined effects of reduced irrigation and water quality on the soil microbial community of a citrus orchard under semi-arid conditions. Soil Biol. Biochem. 2017;104:226–237. doi: 10.1016/j.soilbio.2016.10.024. - DOI
    1. Fereres E., Soriano M.A. Deficit irrigation for reducing agricultural water use. J. Exp. Bot. 2007;58:147–159. doi: 10.1093/jxb/erl165. - DOI - PubMed

LinkOut - more resources