TR32-Database: Database of Transregio 32

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

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Features
Citation
Montzka, C., Moradkhani, H., Weihermüller, L., Hendricks-Franssen, H., Canty, M., Vereecken, H., 2011. Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter. Journal of Hydrology, 399, 410 - 421. DOI: 10.1016/j.jhydrol.2011.01.020.
Identification
Title(s):Main Title: Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter
Description(s):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(s):DOI: 10.1016/j.jhydrol.2011.01.020
Responsible Party
Creator(s):Author: Carsten Montzka
Author: Hamid Moradkhani
Author: Lutz Weihermüller
Author: Harrie-Jan Hendricks-Franssen
Author: Morton Canty
Author: Harry Vereecken
Publisher:Elsevier
Topic
TR32 Topic:Soil
Subject(s):CRC/TR32 Keywords: Soil Moisture, Data Assimilation, Particle Filter, Sequential Importance Resampling, SMOS
File Details
File Name:2011_Montzka_JoH.pdf
Data Type:Text
Size(s):12 Pages
File Size:2246 kB (2.193 MB)
Date(s):Date Accepted: 2011-01-19
Available: 2011-01-26
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:For internal use only
Access Limitations:For internal use only
Licence:TR32DB Data policy agreement
Geographic
North:50.9272430
East:6.3579590
South:50.5797155
West:5.8086426
Measurement Region:NorthRhine-Westphalia
Measurement Location:--NorthRhine-Westphalia--
Specific Informations - Publication
Status:Published
Review:PeerReview
Year:2011
Type:Article
Article Type:Journal
Source:Journal of Hydrology
Volume:399
Number Of Pages:12
Page Range:410 - 421
Metadata Details
Metadata Creator:Carsten Montzka
Metadata Created:2013-12-03
Metadata Last Updated:2013-12-03
Subproject:C6
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:153
Metadata Downloads:0
Dataset Downloads:3
Dataset Activity
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