On the estimation of soil moisture profile and surface fluxes partitioning from sequential assimilation of surface layer soil moisture

Abstract

Recent studies have shown that a variety of remote sensing techniques may be used for the estimation of soil moisture over large areas. The shallow moisture sensing depth of passive microwave measurements, however, limits the use of remotely sensed soil moisture for many land–atmosphere interaction studies. In this study, a method is proposed for soil moisture profile estimation by sequential assimilation of surface layer soil moisture using a four-layer land surface model. A key difference between this and earlier approaches is that it evaluates the relative merits of daily assimilation of microwave measurements of surface soil wetness and measurements of rainfall for the estimation of soil moisture profile. We compare and contrast the profile estimation from assimilation of soil moisture and rainfall measurements using observed data sets from the Kansas prairie in the United States. Influence of measurement error, frequency of assimilation, and availability of precipitation measurements on the estimation of soil moisture profile is also explored.