Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter

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*Title:*	Main Title: Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter
*Description:*	Abstract: 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 study 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 a function of pressure head.
*Identifier:*	10.1016/j.jhydrol.2011.01.020 (DOI)

Responsible Party

*Creators:*	Carsten Montzka (Author), Hamid Moradkhani (Author), Lutz Weihermüller (Author), Harrie-Jan Hendricks-Franssen (Author), Morton Canty (Author), Harry Vereecken (Author)
*Publisher:*	Elsevier
*Publication Year:*	2013

Topic

*TR32 Topic:*	Soil
*Related Subproject:*	C6
*Subjects:*	Keywords: Soil Moisture, Data Assimilation, Particle Filter, Sequential Importance Resampling, SMOS

File Details

*Filename:*	2011_Montzka_JoH.pdf
*Data Type:*	Text - Article
*Size:*	12 Pages
*File Size:*	2.2 MB
*Dates:*	Accepted: 19.01.2011 Available: 26.01.2011
*Mime Type:*	application/pdf
*Data Format:*	PDF
*Language:*	English
*Status:*	Completed

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*Download Permission:*	Only Project Members
*General Access and Use Conditions:*	For internal use only
*Access Limitations:*	For internal use only
*Licence:*	[TR32DB] Data policy agreement

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*Publication Status:*	Published
*Review Status:*	Peer reviewed
*Publication Type:*	Article
*Article Type:*	Journal
*Source:*	Journal of Hydrology
*Source Website:*	www.elsevier.com/locate/jhydrol
*Volume:*	399
*Number of Pages:*	12 (410 - 421)

Metadata Details

*Metadata Creator:*	Carsten Montzka
*Metadata Created:*	03.12.2013
*Metadata Last Updated:*	03.12.2013
*Subproject:*	C6
*Funding Phase:*	2
*Metadata Language:*	English
*Metadata Version:*	V50

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