000864345 001__ 864345
000864345 005__ 20220325143930.0
000864345 0247_ $$2doi$$a10.1002/hyp.13448
000864345 0247_ $$2ISSN$$a0885-6087
000864345 0247_ $$2ISSN$$a1099-1085
000864345 0247_ $$2Handle$$a2128/22575
000864345 0247_ $$2altmetric$$aaltmetric:64097329
000864345 0247_ $$2WOS$$aWOS:000477751000006
000864345 037__ $$aFZJ-2019-04141
000864345 082__ $$a550
000864345 1001_ $$00000-0001-9757-8017$$aSchalge, Bernd$$b0$$eCorresponding author
000864345 245__ $$aImprovement of surface run‐off in the hydrological model ParFlow by a scale‐consistent river parameterization
000864345 260__ $$aNew York, NY$$bWiley$$c2019
000864345 3367_ $$2DRIVER$$aarticle
000864345 3367_ $$2DataCite$$aOutput Types/Journal article
000864345 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1648131006_11907
000864345 3367_ $$2BibTeX$$aARTICLE
000864345 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000864345 3367_ $$00$$2EndNote$$aJournal Article
000864345 520__ $$aWe propose an improvement of the overland‐flow parameterization in a distributed hydrological model, which uses a constant horizontal grid resolution and employs the kinematic wave approximation for both hillslope and river channel flow. The standard parameterization lacks any channel flow characteristics for rivers, which results in reduced river flow velocities for streams narrower than the horizontal grid resolution. Moreover, the surface areas, through which these wider model rivers may exchange water with the subsurface, are larger than the real river channels potentially leading to unrealistic vertical flows. We propose an approximation of the subscale channel flow by scaling Manning's roughness in the kinematic wave formulation via a relationship between river width and grid cell size, following a simplified version of the Barré de Saint‐Venant equations (Manning–Strickler equations). The too large exchange areas between model rivers and the subsurface are compensated by a grid resolution‐dependent scaling of the infiltration/exfiltration rate across river beds. We test both scaling approaches in the integrated hydrological model ParFlow. An empirical relation is used for estimating the true river width from the mean annual discharge. Our simulations show that the scaling of the roughness coefficient and the hydraulic conductivity effectively corrects overland flow velocities calculated on the coarse grid leading to a better representation of flood waves in the river channels.
000864345 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
000864345 588__ $$aDataset connected to CrossRef
000864345 7001_ $$00000-0001-7761-2900$$aHaefliger, Vincent$$b1
000864345 7001_ $$0P:(DE-Juel1)151405$$aKollet, Stefan$$b2
000864345 7001_ $$00000-0003-3001-8642$$aSimmer, Clemens$$b3
000864345 773__ $$0PERI:(DE-600)1479953-4$$a10.1002/hyp.13448$$gp. hyp.13448$$n14$$p2006-2019$$tHydrological processes$$v33$$x1099-1085$$y2019
000864345 8564_ $$uhttps://juser.fz-juelich.de/record/864345/files/Schalge_et_al-2019-Hydrological_Processes.pdf$$yOpenAccess
000864345 8564_ $$uhttps://juser.fz-juelich.de/record/864345/files/Schalge_et_al-2019-Hydrological_Processes.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000864345 909CO $$ooai:juser.fz-juelich.de:864345$$popenaire$$pVDB:Earth_Environment$$pdriver$$pdnbdelivery$$popen_access$$pVDB
000864345 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)151405$$aForschungszentrum Jülich$$b2$$kFZJ
000864345 9131_ $$0G:(DE-HGF)POF3-255$$1G:(DE-HGF)POF3-250$$2G:(DE-HGF)POF3-200$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bErde und Umwelt$$lTerrestrische Umwelt$$vTerrestrial Systems: From Observation to Prediction$$x0
000864345 9141_ $$y2019
000864345 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000864345 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000864345 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bHYDROL PROCESS : 2017
000864345 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000864345 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index
000864345 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000864345 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000864345 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000864345 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences
000864345 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000864345 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz
000864345 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List
000864345 9201_ $$0I:(DE-Juel1)IBG-3-20101118$$kIBG-3$$lAgrosphäre$$x0
000864345 9201_ $$0I:(DE-Juel1)NIC-20090406$$kNIC$$lJohn von Neumann - Institut für Computing$$x1
000864345 980__ $$ajournal
000864345 980__ $$aVDB
000864345 980__ $$aI:(DE-Juel1)IBG-3-20101118
000864345 980__ $$aI:(DE-Juel1)NIC-20090406
000864345 980__ $$aUNRESTRICTED
000864345 9801_ $$aFullTexts