001     14642
005     20200702121552.0
024 7 _ |2 DOI
|a 10.1016/j.jhydrol.2011.01.020
024 7 _ |2 WOS
|a WOS:000288828500024
037 _ _ |a PreJuSER-14642
041 _ _ |a eng
082 _ _ |a 690
084 _ _ |2 WoS
|a Engineering, Civil
084 _ _ |2 WoS
|a Geosciences, Multidisciplinary
084 _ _ |2 WoS
|a Water Resources
100 1 _ |a Montzka, C.
|b 0
|u FZJ
|0 P:(DE-Juel1)VDB51558
245 _ _ |a Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter
260 _ _ |a Amsterdam [u.a.]
|b Elsevier
|c 2011
300 _ _ |a
336 7 _ |a Journal Article
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336 7 _ |a Output Types/Journal article
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336 7 _ |a Journal Article
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336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
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336 7 _ |a article
|2 DRIVER
440 _ 0 |a Journal of Hydrology
|x 0022-1694
|0 3413
|y 3
|v 399
500 _ _ |3 POF3_Assignment on 2016-02-29
500 _ _ |a Record converted from VDB: 12.11.2012
520 _ _ |a In 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.
536 _ _ |a Terrestrische Umwelt
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|x 0
588 _ _ |a Dataset connected to Web of Science
650 _ 7 |a J
|2 WoSType
653 2 0 |2 Author
|a Soil moisture
653 2 0 |2 Author
|a Data assimilation
653 2 0 |2 Author
|a Particle filter
653 2 0 |2 Author
|a Sequential importance resampling
653 2 0 |2 Author
|a HYDRUS-1D
653 2 0 |2 Author
|a SMOS
700 1 _ |a Moradkhani, H.
|b 1
|0 P:(DE-HGF)0
700 1 _ |a Weihermüller, L.
|b 2
|u FZJ
|0 P:(DE-Juel1)VDB17057
700 1 _ |a Hendricks Franssen, H.-J.
|b 3
|u FZJ
|0 P:(DE-Juel1)VDB97935
700 1 _ |a Canty, M.
|b 4
|u FZJ
|0 P:(DE-Juel1)VDB97936
700 1 _ |a Vereecken, H.
|b 5
|u FZJ
|0 P:(DE-Juel1)129549
773 _ _ |a 10.1016/j.jhydrol.2011.01.020
|g Vol. 399
|q 399
|0 PERI:(DE-600)1473173-3
|t Journal of hydrology
|v 399
|y 2011
|x 0022-1694
856 7 _ |u http://dx.doi.org/10.1016/j.jhydrol.2011.01.020
909 C O |o oai:juser.fz-juelich.de:14642
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913 2 _ |a DE-HGF
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|l Terrestrische Umwelt
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914 1 _ |y 2011
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