Application of Electromagnetic Induction to Monitor Changes in Soil Electrical Conductivity Profiles in Arid Agriculture

Handle URI:
http://hdl.handle.net/10754/579543
Title:
Application of Electromagnetic Induction to Monitor Changes in Soil Electrical Conductivity Profiles in Arid Agriculture
Authors:
Jadoon, K.Z.; McCabe, Matthew ( 0000-0002-1279-5272 ) ; Moghadas, D.
Abstract:
In this research, multi-configuration electromagnetic induction (EMI) measurements were conducted in a corn field to estimate variation in soil electrical conductivity profiles in the roots zone. Electromagnetic forward model based on the full solution of Maxwell's equation was used to simulate the apparent electrical conductivity measured with EMI system (the CMD mini-Explorer). Joint inversion of multi-configuration EMI measurements were performed to estimate the vertical soil electrical conductivity profiles. The inversion minimizes the misfit between the measured and modeled soil apparent electrical conductivity by DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is based on Bayesain approach. Results indicate that soil electrical conductivity profiles have low values close to the corn plants, which indicates loss of soil moisture due to the root water uptake. These results offer valuable insights into future potential and emerging challenges in the development of joint analysis of multi-configuration EMI measurements to retrieve effective soil electrical conductivity profiles.
KAUST Department:
Water Desalination and Reuse Research Center (WDRC)
Publisher:
EAGE Publications
Journal:
First Conference on Proximal Sensing Supporting Precision Agriculture
Conference/Event name:
First Conference on Proximal Sensing Supporting Precision Agriculture
Issue Date:
6-Sep-2015
DOI:
10.3997/2214-4609.201413835
Type:
Conference Paper
Additional Links:
http://www.earthdoc.org/publication/publicationdetails/?publication=82430
Appears in Collections:
Conference Papers; Water Desalination and Reuse Research Center (WDRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorJadoon, K.Z.en
dc.contributor.authorMcCabe, Matthewen
dc.contributor.authorMoghadas, D.en
dc.date.accessioned2015-10-11T11:08:46Zen
dc.date.available2015-10-11T11:08:46Zen
dc.date.issued2015-09-06en
dc.identifier.doi10.3997/2214-4609.201413835en
dc.identifier.urihttp://hdl.handle.net/10754/579543en
dc.description.abstractIn this research, multi-configuration electromagnetic induction (EMI) measurements were conducted in a corn field to estimate variation in soil electrical conductivity profiles in the roots zone. Electromagnetic forward model based on the full solution of Maxwell's equation was used to simulate the apparent electrical conductivity measured with EMI system (the CMD mini-Explorer). Joint inversion of multi-configuration EMI measurements were performed to estimate the vertical soil electrical conductivity profiles. The inversion minimizes the misfit between the measured and modeled soil apparent electrical conductivity by DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is based on Bayesain approach. Results indicate that soil electrical conductivity profiles have low values close to the corn plants, which indicates loss of soil moisture due to the root water uptake. These results offer valuable insights into future potential and emerging challenges in the development of joint analysis of multi-configuration EMI measurements to retrieve effective soil electrical conductivity profiles.en
dc.publisherEAGE Publicationsen
dc.relation.urlhttp://www.earthdoc.org/publication/publicationdetails/?publication=82430en
dc.titleApplication of Electromagnetic Induction to Monitor Changes in Soil Electrical Conductivity Profiles in Arid Agricultureen
dc.typeConference Paperen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.identifier.journalFirst Conference on Proximal Sensing Supporting Precision Agricultureen
dc.conference.dateSeptember 06-10, 2015en
dc.conference.nameFirst Conference on Proximal Sensing Supporting Precision Agricultureen
dc.conference.locationTurin, Italyen
dc.eprint.versionPost-printen
dc.contributor.institutionFederal Institute for Geosciences and Natural Resources (BGR), Stilleweg 2, 30655 Hannover, Germanyen
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