Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 64849
Title Assimilation of active microwave observation data for soil moisture profile estimation
Author(s) Hoeben, R.; Troch, P.A.
Source Water Resources Research 36 (2000)10. - ISSN 0043-1397 - p. 2805 - 2819.
Department(s) Hydrology and Quantitative Water Management
Publication type Refereed Article in a scientific journal
Publication year 2000
Keyword(s) bodemwater - retentie - remote sensing - soil water - retention - remote sensing
Categories Remote Sensing
Abstract This paper discusses the potential of retrieving information about the soil moisture profile from measurements of the surface soil moisture content through active microwave observations of the Earth. Recently, Mancini et al. [1999] have shown through laboratory experiments that the volumetric moisture content of the first few centimeters of a bare soil can be determined within 5 ol accuracy by means of C and L band active microwave observations and inverse modeling. Here we use active microwave observations of the surface soil moisture content in a data assimilation framework to show that this allows the retrieval of the root zone soil moisture profile. The data assimilation procedure developed is based on the Kalman filter technique. Kalman filtering allows reconstruction of the state vector of a system when this system is represented by a dynamic model and when at least part of the state variables are observed regularly. The dynamic model of the system used here is based on the one-dimensional Richards equation. The observation equation is based on the Integral Equation Model [Fung et al., 1992; Fung, 1994] and is used to link the radar observations to surface soil moisture content. It is shown that even in the presence of model and observation noise and infrequent observations, accurate retrieval of the entire moisture profile is possible for a bare soil. ? 2000 American Geophysical Union
There are no comments yet. You can post the first one!
Post a comment
Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.