000009700 001__ 9700
000009700 005__ 20190625111341.0
000009700 0247_ $$2DOI$$a10.5194/hess-14-545-2010
000009700 0247_ $$2WOS$$aWOS:000276178100012
000009700 0247_ $$2altmetric$$aaltmetric:1365010
000009700 037__ $$aPreJuSER-9700
000009700 041__ $$aeng
000009700 082__ $$a550
000009700 084__ $$2WoS$$aGeosciences, Multidisciplinary
000009700 084__ $$2WoS$$aWater Resources
000009700 1001_ $$0P:(DE-Juel1)VDB85768$$aRings, J.$$b0$$uFZJ
000009700 245__ $$aCoupled hydrogeophysical parameter estimation using a sequential Bayesian approach
000009700 260__ $$aKatlenburg-Lindau$$bEGU$$c2010
000009700 300__ $$a545 - 556
000009700 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
000009700 3367_ $$2DataCite$$aOutput Types/Journal article
000009700 3367_ $$00$$2EndNote$$aJournal Article
000009700 3367_ $$2BibTeX$$aARTICLE
000009700 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000009700 3367_ $$2DRIVER$$aarticle
000009700 440_0 $$022262$$aHydrology and Earth System Sciences$$v14$$x1027-5606$$y3
000009700 500__ $$aWe thank the reviewers for their constructive comments. J. Rings thanks the BAW Karlsruhe for the possibility to take measurements on the dike model and A. Scheuermann and A. Bieberstein at the IBF, University of Karlsruhe, for supporting the measurements. J. A. Huisman is supported by grant HU1312/21 of the Deutsche Forschungsgemeinschaft.
000009700 520__ $$aCoupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimates. Therefore, we apply a sequential Bayesian framework that provides updates of state, parameters and their uncertainty whenever measurements become available. We have coupled a hydrological and an electrical resistivity tomography (ERT) forward code in a particle filtering framework. First, we analyze a synthetic data set of lysimeter infiltration monitored with ERT. In a second step, we apply the approach to field data measured during an infiltration event on a full-scale dike model. For the synthetic data, the water content distribution and the hydraulic conductivity are accurately estimated after a few time steps. For the field data, hydraulic parameters are successfully estimated from water content measurements made with spatial time domain reflectometry and ERT, and the development of their posterior distributions is shown.
000009700 536__ $$0G:(DE-Juel1)FUEK407$$2G:(DE-HGF)$$aTerrestrische Umwelt$$cP24$$x0
000009700 588__ $$aDataset connected to Web of Science
000009700 650_7 $$2WoSType$$aJ
000009700 7001_ $$0P:(DE-Juel1)129472$$aHuisman, J. A.$$b1$$uFZJ
000009700 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b2$$uFZJ
000009700 773__ $$0PERI:(DE-600)2100610-6$$a10.5194/hess-14-545-2010$$gVol. 14, p. 545 - 556$$p545 - 556$$q14<545 - 556$$tHydrology and earth system sciences$$v14$$x1027-5606$$y2010
000009700 8567_ $$uhttp://dx.doi.org/10.5194/hess-14-545-2010
000009700 909CO $$ooai:juser.fz-juelich.de:9700$$pVDB
000009700 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed
000009700 9141_ $$y2010
000009700 9131_ $$0G:(DE-Juel1)FUEK407$$aDE-HGF$$bErde und Umwelt$$kP24$$lTerrestrische Umwelt$$vTerrestrische Umwelt$$x0
000009700 9201_ $$0I:(DE-Juel1)VDB793$$d31.10.2010$$gICG$$kICG-4$$lAgrosphäre$$x1
000009700 9201_ $$0I:(DE-82)080011_20140620$$gJARA$$kJARA-ENERGY$$lJülich-Aachen Research Alliance - Energy$$x2
000009700 9201_ $$0I:(DE-82)080012_20140620$$kJARA-HPC$$lJARA - HPC$$x3
000009700 970__ $$aVDB:(DE-Juel1)119646
000009700 980__ $$aVDB
000009700 980__ $$aConvertedRecord
000009700 980__ $$ajournal
000009700 980__ $$aI:(DE-Juel1)IBG-3-20101118
000009700 980__ $$aI:(DE-82)080011_20140620
000009700 980__ $$aUNRESTRICTED
000009700 980__ $$aI:(DE-82)080012_20140620
000009700 981__ $$aI:(DE-Juel1)IBG-3-20101118
000009700 981__ $$aI:(DE-Juel1)VDB1047