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000004875 0247_ $$2DOI$$a10.1016/j.jappgeo.2009.03.008
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000004875 084__ $$2WoS$$aGeosciences, Multidisciplinary
000004875 084__ $$2WoS$$aMining & Mineral Processing
000004875 1001_ $$0P:(DE-Juel1)VDB85768$$aRings, J.$$b0$$uFZJ
000004875 245__ $$aReliability of resistivity quantification for shallow subsurface water processes
000004875 260__ $$aKatlenburg-Lindau$$bCopernicus$$c2009
000004875 300__ $$a404 - 416
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000004875 440_0 $$020401$$aAtmospheric Measurement Techniques$$v68$$x1867-1381$$y3
000004875 500__ $$aThe authors thank M. Chouteau and one anonymous reviewer for their constructive comments which largely improved the manuscript. J. Rings acknowledges a grant from the Deutsche Forschungsgemeinschaft in the Postgraduate Programme Natural Disasters (GK 450).
000004875 520__ $$aThe reliability of surface-based electrical resistivity tomography (ERT) for quantifying resistivities for shallow subsurface water processes is analysed. A method comprising numerical simulations of water movement in soil and forward-inverse modeling of ERT surveys for two synthetic data sets is presented. Resistivity contrast, e.g. by changing water content, is shown to have large influence on the resistivity quantification. An ensemble and clustering approach is introduced in which ensembles of 50 different inversion models for one data set are created by randomly varying the parameters for a regularisation based inversion routine. The ensemble members are sorted into five clusters of similar models and the mean model for each cluster is computed. Distinguishing persisting features in the mean models from singular artifacts in individual tomograms can improve the interpretation of inversion results.Especially in the presence of large resistivity contrasts in high sensitivity areas, the quantification of resistivities can be unreliable. The ensemble approach shows that this is an inherent problem present for all models inverted with the regularisation based routine. The results also suggest that the combination of hydrological and electrical modeling might lead to better results. (C) 2009 Elsevier B.V. All rights reserved.
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000004875 65320 $$2Author$$aElectrical resistivity tomography
000004875 65320 $$2Author$$aWater content
000004875 65320 $$2Author$$aEnsembles
000004875 650_7 $$2WoSType$$aJ
000004875 7001_ $$0P:(DE-HGF)0$$aHauck, C. C.$$b1
000004875 773__ $$0PERI:(DE-600)2505596-3$$a10.1016/j.jappgeo.2009.03.008$$gVol. 68, p. 404 - 416$$p404 - 416$$q68<404 - 416$$tAtmospheric measurement techniques$$v68$$x1867-1381$$y2009
000004875 8567_ $$uhttp://dx.doi.org/10.1016/j.jappgeo.2009.03.008
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