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000014642 0247_ $$2DOI$$a10.1016/j.jhydrol.2011.01.020
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000014642 041__ $$aeng
000014642 082__ $$a690
000014642 084__ $$2WoS$$aEngineering, Civil
000014642 084__ $$2WoS$$aGeosciences, Multidisciplinary
000014642 084__ $$2WoS$$aWater Resources
000014642 1001_ $$0P:(DE-Juel1)VDB51558$$aMontzka, C.$$b0$$uFZJ
000014642 245__ $$aHydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter
000014642 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2011
000014642 300__ $$a
000014642 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article
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000014642 440_0 $$03413$$aJournal of Hydrology$$v399$$x0022-1694$$y3
000014642 500__ $$3POF3_Assignment on 2016-02-29
000014642 500__ $$aRecord converted from VDB: 12.11.2012
000014642 520__ $$aIn a synthetic study we explore the potential of using surface soil moisture measurements obtained from different satellite platforms to retrieve soil moisture profiles and soil hydraulic properties using a sequential data assimilation procedure and a 1D mechanistic soil water model. Four different homogeneous soil types were investigated including loamy sand, loam, silt, and clayey soils. The forcing data including precipitation and potential evapotranspiration were taken from the meteorological station of Aachen (Germany). With the aid of the forward model run, a synthetic data set was designed and observations were generated. The virtual top soil moisture observations were then assimilated to update the states and hydraulic parameters of the model by means of a particle filtering data assimilation method. Our analyses include the effect of assimilation strategy, measurement frequency, accuracy in surface soil moisture measurements, and soils differing in textural and hydraulic properties.With this approach we were able to assess the value of periodic spaceborne observations of top soil moisture for soil moisture profile estimation and identify the adequate conditions (e.g. temporal resolution and measurement accuracy) for remotely sensed soil moisture data assimilation. Updating of both hydraulic parameters and state variables allowed better predictions of top soil moisture contents as compared with updating of states only. An important conclusion is that the assimilation of remotely-sensed top soil moisture for soil hydraulic parameter estimation generates a bias depending on the soil type. Results indicate that the ability of a data assimilation system to correct the soil moisture state and estimate hydraulic parameters is driven by the non linearity between soil moisture and pressure head. (c) 2011 Elsevier B.V. All tights reserved.
000014642 536__ $$0G:(DE-Juel1)FUEK407$$2G:(DE-HGF)$$aTerrestrische Umwelt$$cP24$$x0
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000014642 650_7 $$2WoSType$$aJ
000014642 65320 $$2Author$$aSoil moisture
000014642 65320 $$2Author$$aData assimilation
000014642 65320 $$2Author$$aParticle filter
000014642 65320 $$2Author$$aSequential importance resampling
000014642 65320 $$2Author$$aHYDRUS-1D
000014642 65320 $$2Author$$aSMOS
000014642 7001_ $$0P:(DE-HGF)0$$aMoradkhani, H.$$b1
000014642 7001_ $$0P:(DE-Juel1)VDB17057$$aWeihermüller, L.$$b2$$uFZJ
000014642 7001_ $$0P:(DE-Juel1)VDB97935$$aHendricks Franssen, H.-J.$$b3$$uFZJ
000014642 7001_ $$0P:(DE-Juel1)VDB97936$$aCanty, M.$$b4$$uFZJ
000014642 7001_ $$0P:(DE-Juel1)129549$$aVereecken, H.$$b5$$uFZJ
000014642 773__ $$0PERI:(DE-600)1473173-3$$a10.1016/j.jhydrol.2011.01.020$$gVol. 399$$q399$$tJournal of hydrology$$v399$$x0022-1694$$y2011
000014642 8567_ $$uhttp://dx.doi.org/10.1016/j.jhydrol.2011.01.020
000014642 909CO $$ooai:juser.fz-juelich.de:14642$$pVDB$$pVDB:Earth_Environment
000014642 9131_ $$0G:(DE-Juel1)FUEK407$$bErde und Umwelt$$kP24$$lTerrestrische Umwelt$$vTerrestrische Umwelt$$x0
000014642 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
000014642 9141_ $$y2011
000014642 915__ $$0StatID:(DE-HGF)0010$$aJCR/ISI refereed
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