Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/26429

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Title
Three-dimensional soil moisture profile retrieval by assimilation of near-surface measurements: simplified kalman filter covariance forecasting and field application
Author/Creator
Walker, Jeffrey P.;  Willgoose, Garry R.;  Kalma, Jetse D.
Description
The Kalman filter data assimilation technique is applied to a distributed three-dimensional soil moisture model for retrieval of the soil moisture profile in a 6 ha catchment using near-surface soil moisture measurements. A simplified Kalman filter covariance forecasting methodology is developed based on forecasting of the state correlations and imposed state variances. This covariance forecasting technique, termed the modified Kalman filter, was then used in a 1 month three-dimensional field application. Two updating scenarios were tested: (1) updating every 2 to 3 days and (2) a single update. The data used were from the Nerrigundah field site, near Newcastle, Australia. This study demonstrates the feasibility of data assimilation in a quasi three-dimensional distributed soil moisture model, provided simplified covariance forecasting techniques are used. It also identifies that (1) the soil moisture profile cannot be retrieved from near-surface soil moisture measurements when the near-surface and deep soil layers become decoupled, such as during extreme drying events; (2) if simulation of the soil moisture profile is already good, the assimilation can result in a slight degradation, but if the simulation is poor, assimilation can yield a significant improvement; (3) soil moisture profile retrieval results are independent of initial conditions; and (4) the required update frequency is a function of the errors in model physics and forcing data.
Relation
Water Resources Research Vol. 38, Issue 12, p. 37-1 to 37-13
Publisher Link
http://dx.doi.org/10.1029/2002WR001545
Date
2002
Publisher
American Geophysical Union
Keyword(s)
soil moisture;  remote sensing;  data assimilation;  catchment hydrology;  field study;  covariance estimation
Resource Type
journal article
Identifier
http://hdl.handle.net/1959.13/26429
Identifier
ISSN:0043-1397
Reviewed
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Subject
"Water Resources Research"
 
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