Assimilating remote sensing data in a surface flux–soil moisture model

A key state variable in land surface–atmosphere interactions is soil moisture, which affects surface energy fluxes, runoff and the radiation balance. Soil moisture modelling relies on parameter estimates that are inadequately measured at the necessarily fine model scales. Hence, model soil moisture estimates are imperfect and often drift away from reality through simulation time. Because of its spatial and temporal nature, remote sensing holds great promise for soil moisture estimation. Much success has been attained in recent years in soil moisture estimation using passive and active microwave sensors, but progress has been slow. One reason for this is the scale disparity between remote sensing data resolution and the hydrologic process scale. Other impediments include vegetation cover and microwave penetration depth. As a result, currently there is no comprehensive method for assimilating remote soil moisture observations within a surface hydrology model at watershed or larger scales. This paper describes a measurement–modelling system for estimating the three-dimensional soil moisture distribution, incorporating remote microwave observations, a surface flux–soil moisture model, a radiative transfer model and Kalman filtering. The surface model, driven by meteorological observations, estimates the vertical and lateral distribution of water. Based on the model soil moisture profiles, microwave brightness temperatures are estimated using the radiative transfer model. A Kalman filter is then applied using modelled and observed brightness temperatures to update the model soil moisture profile. The modelling system has been applied using data from the Southern Great Plains 1997 field experiment. In the presence of highly inaccurate rainfall input, assimilation of remote microwave data results in better agreement with observed soil moisture. Without assimilation, it was seen that the model near-surface soil moisture reached a minimum that was higher than observed, resulting in substantial errors during very dry conditions. Updating moisture profiles daily with remotely sensed brightness temperatures reduced but did not eliminate this bias. Copyright  2002 John Wiley & Sons, Ltd.

[1]  K. Y. Li,et al.  Towards Estimating Soil Moisture in the Root Zone Using Remotely Sensed Surface Data , 1998 .

[2]  Thomas J. Jackson,et al.  Soil moisture mapping at regional scales using microwave radiometry: the Southern Great Plains Hydrology Experiment , 1999, IEEE Trans. Geosci. Remote. Sens..

[3]  D. Vidal-Madjar,et al.  Evaporation From a Bare Soil Evaluated Using a Soil Water Transfer Model and Remotely Sensed Surface Soil Moisture Data , 1984 .

[4]  Dara Entekhabi,et al.  Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations , 1994, IEEE Trans. Geosci. Remote. Sens..

[5]  G. Hornberger,et al.  Empirical equations for some soil hydraulic properties , 1978 .

[6]  F. R. Schiebe,et al.  Large area mapping of soil moisture using the ESTAR passive microwave radiometer , 1995 .

[7]  J. R. Eagleman,et al.  Remote sensing of soil moisture by a 21-cm passive radiometer. [onboard Skylab] , 1976 .

[8]  B. Choudhury,et al.  Effect of surface roughness on the microwave emission from soils , 1979 .

[9]  J. Kong,et al.  Theory for passive microwave remote sensing of near‐surface soil moisture , 1977 .

[10]  Dara Entekhabi,et al.  Tests of sequential data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness , 1999, IEEE Trans. Geosci. Remote. Sens..

[11]  E. Smith,et al.  Estimation of surface heat and moisture fluxes over a prairie grassland: 3. Design of a hybrid physical/remote sensing biosphere model , 1993 .

[12]  T. Schmugge,et al.  Vegetation effects on the microwave emission of soils , 1991 .

[13]  T. Carlson,et al.  Estimating near-surface soil moisture availability using a meteorologically driven soil-water profile model , 1994 .

[14]  T. Schmugge,et al.  Passive microwave remote sensing system for soil moisture: some supporting research , 1989 .

[15]  Richard A. Brown,et al.  Introduction to random signals and applied kalman filtering (3rd ed , 2012 .

[16]  W. J. Shuttleworth,et al.  Integration of soil moisture remote sensing and hydrologic modeling using data assimilation , 1998 .

[17]  E. Engman,et al.  Status of microwave soil moisture measurements with remote sensing , 1995 .

[18]  Charles A. Laymon,et al.  Defining the range of uncertainty associated with remotely sensed soil moisture estimates with microwave radiometers , 1999, Remote Sensing.

[19]  M. Vauclin,et al.  Possible use of active microwave remote sensing data for prediction of regional evaporation by Numerical simulation of soil water movement in the unsaturated zone , 1981 .

[20]  R. Dickinson,et al.  Biosphere-Atmosphere Transfer Scheme (BATS) version le as coupled to the NCAR community climate model. Technical note. [NCAR (National Center for Atmospheric Research)] , 1993 .

[21]  F. Ulaby,et al.  Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Thomas J. Jackson,et al.  Passive microwave observation of diurnal surface soil moisture , 1997, IEEE Trans. Geosci. Remote. Sens..

[23]  Michael Robert Smith.  The prediction of root zone soil moisture with a water balance - microwave emission model , 1983 .