000138284 001__ 138284
000138284 005__ 20210129212212.0
000138284 0247_ $$2doi$$a10.5194/hess-17-3795-2013
000138284 0247_ $$2ISSN$$a1027-5606
000138284 0247_ $$2ISSN$$a1607-7938
000138284 0247_ $$2WOS$$aWOS:000326603200008
000138284 0247_ $$2Handle$$a2128/11508
000138284 037__ $$aFZJ-2013-04441
000138284 082__ $$a550
000138284 1001_ $$0P:(DE-Juel1)140349$$aKurtz, W.$$b0$$eCorresponding author$$ufzj
000138284 245__ $$aIs high-resolution inverse characterization of heterogeneous river bed hydraulic conductivities needed and possible?
000138284 260__ $$aKatlenburg-Lindau$$bEGU$$c2013
000138284 3367_ $$2DRIVER$$aarticle
000138284 3367_ $$2DataCite$$aOutput Types/Journal article
000138284 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1381307623_25898
000138284 3367_ $$2BibTeX$$aARTICLE
000138284 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000138284 3367_ $$00$$2EndNote$$aJournal Article
000138284 500__ $$3POF3_Assignment on 2016-02-29
000138284 520__ $$aRiver–aquifer exchange fluxes influence local and regional water balances and affect groundwater and river water quality and quantity. Unfortunately, river–aquifer exchange fluxes tend to be strongly spatially variable, and it is an open research question to which degree river bed heterogeneity has to be represented in a model in order to achieve reliable estimates of river–aquifer exchange fluxes. This research question is addressed in this paper with the help of synthetic simulation experiments, which mimic the Limmat aquifer in Zurich (Switzerland), where river–aquifer exchange fluxes and groundwater management activities play an important role. The solution of the unsaturated–saturated subsurface hydrological flow problem including river–aquifer interaction is calculated for ten different synthetic realities where the strongly heterogeneous river bed hydraulic conductivities (L) are perfectly known. Hydraulic head data (100 in the default scenario) are sampled from the synthetic realities. In subsequent data assimilation experiments, where L is unknown now, the hydraulic head data are used as conditioning information, with the help of the ensemble Kalman filter (EnKF). For each of the ten synthetic realities, four different ensembles of L are tested in the experiments with EnKF; one ensemble estimates high-resolution L fields with different L values for each element, and the other three ensembles estimate effective L values for 5, 3 or 2 zones. The calibration of higher-resolution L fields (i.e. fully heterogeneous or 5 zones) gives better results than the calibration of L for only 3 or 2 zones in terms of reproduction of states, stream–aquifer exchange fluxes and parameters. Effective L for a limited number of zones cannot always reproduce the true states and fluxes well and results in biased estimates of net exchange fluxes between aquifer and stream. Also in case only 10 head data are used for conditioning, the high-resolution characterization of L fields with EnKF is still feasible. For less heterogeneous river bed hydraulic conductivities, a high-resolution characterization of L is less important. When uncertainties in the hydraulic parameters of the aquifer are also regarded in the assimilation, the errors in state and flux predictions increase, but the ensemble with a high spatial resolution for L still outperforms the ensembles with effective L values. We conclude that for strongly heterogeneous river beds the commonly applied simplified representation of the streambed, with spatially homogeneous parameters or constant parameters for a few zones, might yield significant biases in the characterization of the water balance. For strongly heterogeneous river beds, we suggest adopting a stochastic field approach to model the spatially heterogeneous river beds geostatistically. The paper illustrates that EnKF is able to calibrate such heterogeneous streambeds on the basis of hydraulic head measurements, outperforming zonation approaches.
000138284 536__ $$0G:(DE-HGF)POF2-246$$a246 - Modelling and Monitoring Terrestrial Systems: Methods and Technologies (POF2-246)$$cPOF2-246$$fPOF II$$x0
000138284 588__ $$aDataset connected to CrossRef, juser.fz-juelich.de
000138284 7001_ $$0P:(DE-Juel1)138662$$aHendricks Franssen, H. -J.$$b1$$ufzj
000138284 7001_ $$0P:(DE-HGF)0$$aBrunner, P.$$b2
000138284 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b3$$ufzj
000138284 773__ $$0PERI:(DE-600)2100610-6$$a10.5194/hess-17-3795-2013$$gVol. 17, no. 10, p. 3795 - 3813$$n10$$p3795 - 3813$$tHydrology and earth system sciences$$v17$$x1027-5606
000138284 8564_ $$uhttp://www.hydrol-earth-syst-sci.net/17/3795/2013/hess-17-3795-2013.html
000138284 8564_ $$uhttps://juser.fz-juelich.de/record/138284/files/FZJ-2013-04441.pdf$$yOpenAccess
000138284 909CO $$ooai:juser.fz-juelich.de:138284$$pdnbdelivery$$pVDB$$pVDB:Earth_Environment$$pdriver$$popen_access$$popenaire
000138284 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)140349$$aForschungszentrum Jülich GmbH$$b0$$kFZJ
000138284 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)138662$$aForschungszentrum Jülich GmbH$$b1$$kFZJ
000138284 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$aExternal Institute$$b2$$kExtern
000138284 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129549$$aForschungszentrum Jülich GmbH$$b3$$kFZJ
000138284 9132_ $$0G:(DE-HGF)POF3-259H$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$aDE-HGF$$bMarine, Küsten- und Polare Systeme$$lTerrestrische Umwelt$$vAddenda$$x0
000138284 9131_ $$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$$x0
000138284 9141_ $$y2013
000138284 915__ $$0LIC:(DE-HGF)CCBY3$$2HGFVOC$$aCreative Commons Attribution CC BY 3.0
000138284 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000138284 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record
000138284 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR
000138284 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000138284 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000138284 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000138284 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000138284 915__ $$0StatID:(DE-HGF)0010$$2StatID$$aJCR/ISI refereed
000138284 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000138284 920__ $$lyes
000138284 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000138284 980__ $$ajournal
000138284 980__ $$aVDB
000138284 980__ $$aUNRESTRICTED
000138284 980__ $$aI:(DE-Juel1)IBG-3-20101118
000138284 9801_ $$aFullTexts