TR32-Database: Database of Transregio 32

[1450] - Large-scale multi-configuration electromagnetic induction: a promising tool to improve hydrological models

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Features
Citation
von Hebel, C., Rudolph, S., Mester, A., Huisman, J. A., Montzka, C., Weihermüller, L., Vereecken, H., van der Kruk, J., 2015. Large-scale multi-configuration electromagnetic induction: a promising tool to improve hydrological models. EGU General Assembly 2015, April 12 - 17, 2015, Vienna. Accessed from http://www.tr32db.uni-koeln.de/data.php?dataID=1450 at 2017-09-24.
Identification
Title(s):Main Title: Large-scale multi-configuration electromagnetic induction: a promising tool to improve hydrological models
Description(s):Abstract: Large-scale multi-configuration electromagnetic induction (EMI) use different coil configurations, i.e., coil offsets and coil orientations, to sense coil specific depth volumes. The obtained apparent electrical conductivity (ECa) maps can be related to some soil properties such as clay content, soil water content, and pore water conductivity, which are important characteristics that influence hydrological processes. Here, we use large-scale EMI measurements to investigate changes in soil texture that drive the available water supply causing crop development patterns that were observed in leaf area index (LAI) maps obtained from RapidEye satellite images taken after a drought period. The 20 ha test site is situated within the Ellebach catchment (Germany) and consists of a sand-and-gravel dominated upper terrace (UT) and a loamy lower terrace (LT). The large-scale multi-configuration EMI measurements were calibrated using electrical resistivity tomography (ERT) measurements at selected transects and soil samples were taken at representative locations where changes in the electrical conductivity were observed and therefore changing soil properties were expected. By analyzing all the data, the observed LAI patterns could be attributed to buried paleo-river channel systems that contained a higher silt and clay content and provided a higher water holding capacity than the surrounding coarser material. Moreover, the measured EMI data showed highest correlation with LAI for the deepest sensing coil offset (up to 1.9 m), which indicates that the deeper subsoil is responsible for root water uptake especially under drought conditions. To obtain a layered subsurface electrical conductivity model that shows the subsurface structures more clearly, a novel EMI inversion scheme was applied to the field data. The obtained electrical conductivity distributions were validated with soil probes and ERT transects that confirmed the inverted lateral and vertical large-scale electrical conductivity model. These results show that multi-configuration EMI data provide detailed subsurface information up to several meters depth that can be used to improve hydrological process understanding.
Responsible Party
Creator(s):Author: Christian von Hebel
Author: Sebastian Rudolph
Author: Achim Mester
Author: Johan A. Huisman
Author: Carsten Montzka
Author: Lutz Weihermüller
Author: Harry Vereecken
Author: Jan van der Kruk
Publisher:CRC/TR32 Database (TR32DB)
Topic
TR32 Topic:Soil
Related Sub-project(s):B6
Subject(s):CRC/TR32 Keywords: Soil
File Details
File Name:CvH_EMI_EGU2015.pptx
Data Type:Event
File Size:55122 kB (53.83 MB)
Date(s):Issued: 2015-04-13
Mime Type:application/vnd.openxmlformats-officedocument.presentationml.presentation
Data Format:MS PowerPoint
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:Ellebach
Measurement Location:Selhausen
Specific Informations - Presentation
Presenter:von Hebel
Presentation Date:2015-04-13
Presentation Type:Talk
Event Name:EGU General Assembly 2015
Event Type:Conference
Event Location:Vienna
Event Period:12th of April, 2015 - 17th of April, 2015
Metadata Details
Metadata Creator:Christian von Hebel
Metadata Created:2016-10-12
Metadata Last Updated:2016-10-12
Subproject:B6
Funding Phase:3
Metadata Language:English
Metadata Version:V41
Dataset Metrics
Page Visits:162
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Features