Quasi-3D mapping of soil moisture in agricultural fields using electrical conductivity sensing

Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and min...

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Vydáno v:	Agricultural water management Ročník 259; s. 107246
Hlavní autoři:	Shaukat, Hira, Flower, Ken C., Leopold, Matthias
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.01.2022
Témata:	algorithms Crop rotation dry season electrical conductivity Electrical resistivity tomography EM inversion laboratory experimentation neutrons prediction soil depth soil profiles Soil volumetric water content soil water volumetric water content water management wet season Electrical resistivity tomography EM inversion Soil volumetric water content Crop rotation
ISSN:	0378-3774, 1873-2283
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Abstract	Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and minimal soil intrusion. So far, EMI has mainly been used for homogenous soil conditions, which are not common in agriculture and results are mainly validated by excavated pits or calibration models using soil samples on a transect. This study converts apparent electrical conductivity data recorded with a Dualem-1Hs EM-metre for two surveys of variable moisture conditions (dry and wet season) with 2475 and 2174 data points over 5.4 ha, in a field with a contrasting vertical soil profile into spatiotemporal management zones. A least square inversion algorithm was used to determine electrical conductivities for individual soil layers of 0–0.5 m, 0.5–0.8 m and 0.8–1.6 m. Soil samples from the depth of 0.5 m and 0.8 m were used for soil moisture calibrations. A laboratory experiment under controlled conditions developed electric conductivity vs volumetric water content relations with power law functions for required soil depth slices with R2 values between 0.98 and 0.99. Subsequently, EMI data were converted to volumetric water contents for each layer and predictions were spatially displayed. Median change between the measured apparent conductivity and inverted values range from 6 to 17 mS m-1 resulting in 3–7% difference in volumetric water prediction. These EMI based soil moisture predictions were compared with neutron moisture metre measurements, with Pearson R values of 0.74 and 0.95 for the wet and dry season surveys, respectively. The method is robust and offers a comparatively fast method to estimate the soil moisture status in fields and subsequently make informed management decisions. •An electromagnetic induction survey was used for field soil moisture prediction.•Electrical resistivity–soil moisture calibrations were established for two depths.•The calibrations were used to convert soil conductivity to volumetric moisture.•Soil moisture was accurately predicted at three depths for dry and wet seasons.•Inversion improved soil moisture estimation over the soil profile.
AbstractList	Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and minimal soil intrusion. So far, EMI has mainly been used for homogenous soil conditions, which are not common in agriculture and results are mainly validated by excavated pits or calibration models using soil samples on a transect. This study converts apparent electrical conductivity data recorded with a Dualem-1Hs EM-metre for two surveys of variable moisture conditions (dry and wet season) with 2475 and 2174 data points over 5.4 ha, in a field with a contrasting vertical soil profile into spatiotemporal management zones. A least square inversion algorithm was used to determine electrical conductivities for individual soil layers of 0–0.5 m, 0.5–0.8 m and 0.8–1.6 m. Soil samples from the depth of 0.5 m and 0.8 m were used for soil moisture calibrations. A laboratory experiment under controlled conditions developed electric conductivity vs volumetric water content relations with power law functions for required soil depth slices with R² values between 0.98 and 0.99. Subsequently, EMI data were converted to volumetric water contents for each layer and predictions were spatially displayed. Median change between the measured apparent conductivity and inverted values range from 6 to 17 mS m⁻¹ resulting in 3–7% difference in volumetric water prediction. These EMI based soil moisture predictions were compared with neutron moisture metre measurements, with Pearson R values of 0.74 and 0.95 for the wet and dry season surveys, respectively. The method is robust and offers a comparatively fast method to estimate the soil moisture status in fields and subsequently make informed management decisions. Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Recent advances in non-invasive electromagnetic induction (EMI) techniques have created an opportunity to determine soil moisture content with high-resolution and minimal soil intrusion. So far, EMI has mainly been used for homogenous soil conditions, which are not common in agriculture and results are mainly validated by excavated pits or calibration models using soil samples on a transect. This study converts apparent electrical conductivity data recorded with a Dualem-1Hs EM-metre for two surveys of variable moisture conditions (dry and wet season) with 2475 and 2174 data points over 5.4 ha, in a field with a contrasting vertical soil profile into spatiotemporal management zones. A least square inversion algorithm was used to determine electrical conductivities for individual soil layers of 0–0.5 m, 0.5–0.8 m and 0.8–1.6 m. Soil samples from the depth of 0.5 m and 0.8 m were used for soil moisture calibrations. A laboratory experiment under controlled conditions developed electric conductivity vs volumetric water content relations with power law functions for required soil depth slices with R2 values between 0.98 and 0.99. Subsequently, EMI data were converted to volumetric water contents for each layer and predictions were spatially displayed. Median change between the measured apparent conductivity and inverted values range from 6 to 17 mS m-1 resulting in 3–7% difference in volumetric water prediction. These EMI based soil moisture predictions were compared with neutron moisture metre measurements, with Pearson R values of 0.74 and 0.95 for the wet and dry season surveys, respectively. The method is robust and offers a comparatively fast method to estimate the soil moisture status in fields and subsequently make informed management decisions. •An electromagnetic induction survey was used for field soil moisture prediction.•Electrical resistivity–soil moisture calibrations were established for two depths.•The calibrations were used to convert soil conductivity to volumetric moisture.•Soil moisture was accurately predicted at three depths for dry and wet seasons.•Inversion improved soil moisture estimation over the soil profile.
ArticleNumber	107246
Author	Shaukat, Hira Flower, Ken C. Leopold, Matthias
Author_xml	– sequence: 1 givenname: Hira surname: Shaukat fullname: Shaukat, Hira organization: UWA School of Agriculture and Environment, soil matrix group, The University of Western Australia, Stirling Highway, Crawley, WA 6009, Australia – sequence: 2 givenname: Ken C. surname: Flower fullname: Flower, Ken C. organization: UWA School of Agriculture and Environment, soil matrix group, The University of Western Australia, Stirling Highway, Crawley, WA 6009, Australia – sequence: 3 givenname: Matthias surname: Leopold fullname: Leopold, Matthias email: matthias.leopold@uwa.edu.au organization: UWA School of Agriculture and Environment, soil matrix group, The University of Western Australia, Stirling Highway, Crawley, WA 6009, Australia
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Snippet	Knowledge of real time spatial distribution of soil moisture has great potential to improve yield and profit in agricultural systems. Recent advances in...
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SubjectTerms	algorithms Crop rotation dry season electrical conductivity Electrical resistivity tomography EM inversion laboratory experimentation neutrons prediction soil depth soil profiles Soil volumetric water content soil water volumetric water content water management wet season
Title	Quasi-3D mapping of soil moisture in agricultural fields using electrical conductivity sensing
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