A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields

Abstract Soil moisture information is a key variable for guiding in‐season management decisions in rainfed and irrigated agricultural systems. However, methods for deciding the number and location of soil moisture sensors (SMS) per field still remain poorly explored in the scientific literature. The...

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Autores principales:	Pedro R. Rossini, Ignacio Antonio Ciampitti, Trevor Hefley, Andres Patrignani
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Environmental sciences GE1-350 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/7b005804783d4769b140eaee6c029be7
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spelling	oai:doaj.org-article:7b005804783d4769b140eaee6c029be72021-11-25T13:30:33ZA soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields1539-166310.1002/vzj2.20159https://doaj.org/article/7b005804783d4769b140eaee6c029be72021-11-01T00:00:00Zhttps://doi.org/10.1002/vzj2.20159https://doaj.org/toc/1539-1663Abstract Soil moisture information is a key variable for guiding in‐season management decisions in rainfed and irrigated agricultural systems. However, methods for deciding the number and location of soil moisture sensors (SMS) per field still remain poorly explored in the scientific literature. The goal of this study was to evaluate a quantitative framework based on soil moisture‐based management zones (MZs) to determine the minimum number and tentative deployment location of SMS. Multiple spatially intensive (n > 100 observations) surveys of near‐surface (0–12 cm) soil moisture were conducted during the fallow periods and early growing seasons of 2017, 2018, and 2019 on three agricultural fields using a calibrated handheld soil water reflectometer. The fuzzy C‐means (FCM) clustering method was used to delineate MZs based on the soil moisture surveys, and the silhouette clustering evaluation method was used to identify the optimal number of MZs per field. Then, a sensor location index that considered the distance to the MZ boundaries and the FCM membership grade was developed to identify the tentative optimal deployment location of SMS. The proposed method effectively identified field areas with distinct soil moisture regimes and revealed the complex soil moisture spatial patterns that were not captured with elevation or soil texture alone. Dividing the fields using soil moisture‐based MZ reduced the intrazone soil moisture spatial variability by about 50% compared with that of the entire field. In the three studied fields, a total of two SMS were sufficient to capture the salient soil moisture spatial regimes.Pedro R. RossiniIgnacio Antonio CiampittiTrevor HefleyAndres PatrignaniWileyarticleEnvironmental sciencesGE1-350GeologyQE1-996.5ENVadose Zone Journal, Vol 20, Iss 6, Pp n/a-n/a (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Environmental sciences GE1-350 Geology QE1-996.5
spellingShingle	Environmental sciences GE1-350 Geology QE1-996.5 Pedro R. Rossini Ignacio Antonio Ciampitti Trevor Hefley Andres Patrignani A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
description	Abstract Soil moisture information is a key variable for guiding in‐season management decisions in rainfed and irrigated agricultural systems. However, methods for deciding the number and location of soil moisture sensors (SMS) per field still remain poorly explored in the scientific literature. The goal of this study was to evaluate a quantitative framework based on soil moisture‐based management zones (MZs) to determine the minimum number and tentative deployment location of SMS. Multiple spatially intensive (n > 100 observations) surveys of near‐surface (0–12 cm) soil moisture were conducted during the fallow periods and early growing seasons of 2017, 2018, and 2019 on three agricultural fields using a calibrated handheld soil water reflectometer. The fuzzy C‐means (FCM) clustering method was used to delineate MZs based on the soil moisture surveys, and the silhouette clustering evaluation method was used to identify the optimal number of MZs per field. Then, a sensor location index that considered the distance to the MZ boundaries and the FCM membership grade was developed to identify the tentative optimal deployment location of SMS. The proposed method effectively identified field areas with distinct soil moisture regimes and revealed the complex soil moisture spatial patterns that were not captured with elevation or soil texture alone. Dividing the fields using soil moisture‐based MZ reduced the intrazone soil moisture spatial variability by about 50% compared with that of the entire field. In the three studied fields, a total of two SMS were sufficient to capture the salient soil moisture spatial regimes.
format	article
author	Pedro R. Rossini Ignacio Antonio Ciampitti Trevor Hefley Andres Patrignani
author_facet	Pedro R. Rossini Ignacio Antonio Ciampitti Trevor Hefley Andres Patrignani
author_sort	Pedro R. Rossini
title	A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
title_short	A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
title_full	A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
title_fullStr	A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
title_full_unstemmed	A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
title_sort	soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/7b005804783d4769b140eaee6c029be7
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A soil moisture‐based framework for guiding the number and location of soil moisture sensors in agricultural fields

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