Nonlinear models for soil moisture sensor calibrat... - BV FAPESP
Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Nonlinear models for soil moisture sensor calibration in tropical mountainous soils

Full text
Author(s):
Christofaro Silva, Barbara Pereira [1] ; Tassinari, Diego [2] ; Naves Silva, Marx Leandro [2] ; Silva, Bruno Montoani [2] ; Curi, Nilton [2] ; da Rocha, Humberto Ribeiro [3]
Total Authors: 6
Affiliation:
[1] Inst Fed Educ Ciencia & Tecnol Para, Av Prefeito Nelson Souza, BR-68250000 Obidos, PA - Brazil
[2] Univ Fed Lavras, Dept Ciencia Solo, Av Dr Sylvio Menicucci 1001, BR-37200900 Lavras, MG - Brazil
[3] Univ Sao Paulo, IAG, Dept Ciencias Atmosfer, R do Matao 1226, BR-05508090 Sao Paulo, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: Scientia Agricola; v. 79, n. 4 2022.
Web of Science Citations: 0
Abstract

ABSTRACT Electromagnetic sensors are widely used to monitor soil water content (θ); however, site-specific calibrations are necessary for accurate measurements. This study compares regression models used for calibration of soil moisture sensors and investigates the relation between soil attributes and the adjusted parameters of the specific calibration equations. Undisturbed soil samples were collected in the A and B horizons of two Ultisols and two Inceptisols from the Mantiqueira Range in Southeastern Brazil. After saturation, the Theta Probe ML2X was used to obtain the soil dielectric constant (ε). Several readings were made, ranging from saturation to oven-dry. After each reading, the samples were weighted to calculate θ (m3 m–3). Fourteen regression models (linear, linearized, and nonlinear) were adjusted to the calibration data and checked for their residue distribution. Only the exponential model with three parameters met the regression assumptions regarding residue distribution. The stepwise regression was used to obtain multiple linear equations to estimate the adjusted parameters of the calibration model from soil attributes, with silt and clay contents providing the best relations. Both the specific and the general calibrations performed well, with RMSE values of 0.02 and 0.03 m3 m–3, respectively. Manufacturer calibration and equations from the literature were much less accurate, reinforcing the need to develop specific calibrations. (AU)

FAPESP's process: 17/50241-5 - Brazilian experimental datasets for multi scale interactions in the critical zone under extreme drought
Grantee:Humberto Ribeiro da Rocha
Support Opportunities: Regular Research Grants
FAPESP's process: 19/23853-5 - Regional risks and opportunities on land use change and climate change with thermal-water ecosystem services: investigation for basins in Caatinga and Atlantic Forest
Grantee:Humberto Ribeiro da Rocha
Support Opportunities: Regular Research Grants