000172405 001__ 172405
000172405 005__ 20210129214429.0
000172405 0247_ $$2doi$$a10.1007/s12665-014-3240-7
000172405 0247_ $$2WOS$$aWOS:000341085400005
000172405 037__ $$aFZJ-2014-05885
000172405 082__ $$a550
000172405 1001_ $$0P:(DE-Juel1)136836$$aAltdorff, Daniel$$b0$$eCorresponding Author$$ufzj
000172405 245__ $$aDelineation of areas with different temporal behavior of soilproperties at a landslide affected Alpine hillside using time-lapseelectromagnetic data
000172405 260__ $$aBerlin$$bSpringer$$c2014
000172405 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1415874329_22428
000172405 3367_ $$2DataCite$$aOutput Types/Journal article
000172405 3367_ $$00$$2EndNote$$aJournal Article
000172405 3367_ $$2BibTeX$$aARTICLE
000172405 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000172405 3367_ $$2DRIVER$$aarticle
000172405 520__ $$aLandslide activity is largely controlled bychanges in soil properties, particularly soil moisture and thecorresponding changes in pore pressure within the vadosezone. While knowledge of changes in soil conditions is ofutmost importance for the prediction of landslides, it isdifficult to obtain reliable information on the field scale. Apossibility of filling that information gap is the monitoringof changes in soil properties by time-lapse electromagneticinduction (EMI) data. Given the relative stability of soilproperties, changes in apparent electric conductivity (ECa)are mainly related to changes in soil water content and itsmineralization. Thus, we use time-lapse ECa data over anine-month period from different investigation depths(0.75, 1.5, 3, and 6 m) to separate areas with differenttemporal behavior of soil properties. However, workingwith time-lapse EMI data raised the comparability problemsince the recoded ECa is also affected by several dayspecificsurvey conditions (e.g., instrument temperature,operator). Consequently, the reproducibility of accurateECa measurements is difficult due to potential dynamicshifts which hinders a direct comparing. We introduce inthis study a straightforward method for comparability ofECa values from different time steps by normalization ofdata ranges assuming that the majority of shifts of measureddata originate from field calibration. We identify theintensity of spatial changes by means of the standarddeviation (SD) as an indication for the intensity of soilproperties variability. To obtain the temporal changes andits progression over time, we separate the dynamic signalfrom the background. A two-layer system could be identified:one shallow more dynamic layer with an east–westorientedstructure and a deeper, more stationary layer witha north–south-oriented structure. The ECa dynamics of theshallow layer is related to the altitude (R2 = 0.84) whilethe deeper dynamics follow a different regime. Thedecreasing of ECa dynamics with depth was consistentwith the decreasing of SWC dynamics observed by previousstudies.
000172405 536__ $$0G:(DE-HGF)POF2-246$$a246 - Modelling and Monitoring Terrestrial Systems: Methods and Technologies (POF2-246)$$cPOF2-246$$fPOF II$$x0
000172405 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x1
000172405 7001_ $$0P:(DE-HGF)0$$aDietrich, Peter$$b1
000172405 773__ $$0PERI:(DE-600)2493699-6$$a10.1007/s12665-014-3240-7$$n5$$p1357-1366$$tEnvironmental earth sciences$$v72$$x1866-6280$$y2014
000172405 8564_ $$uhttps://juser.fz-juelich.de/record/172405/files/FZJ-2014-05885.pdf$$yRestricted
000172405 909CO $$ooai:juser.fz-juelich.de:172405$$pVDB:Earth_Environment$$pVDB
000172405 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)136836$$aForschungszentrum Jülich GmbH$$b0$$kFZJ
000172405 9132_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$aDE-HGF$$bPOF III$$lMarine, Küsten- und Polare Systeme$$vTerrestrische Umwelt$$x0
000172405 9131_ $$0G:(DE-HGF)POF2-246$$1G:(DE-HGF)POF2-240$$2G:(DE-HGF)POF2-200$$3G:(DE-HGF)POF2$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vModelling and Monitoring Terrestrial Systems: Methods and Technologies$$x0
000172405 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF3-255$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x1
000172405 9141_ $$y2014
000172405 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR
000172405 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000172405 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000172405 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000172405 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000172405 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews
000172405 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences
000172405 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF <  5
000172405 920__ $$lyes
000172405 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000172405 980__ $$ajournal
000172405 980__ $$aVDB
000172405 980__ $$aI:(DE-Juel1)IBG-3-20101118
000172405 980__ $$aUNRESTRICTED