Submitted to: Advances in Water Resources
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 18, 2009
Publication Date: May 1, 2010
Citation: Li, F., Crow, W.T., Kustas, W.P. 2010. Estimating root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals. Advances in Water Resources. 33:201-214. Interpretive Summary: Accurate information regarding the quantity of soil water within the surface root zone (commonly defined as the top 1 meter of soil column) is valuable for a wide range of agricultural applications (including irrigation scheduling, fertilizer application optimization and crop yield forecasting). This research looks at ways to combine three distinct methodologies for tracking the availability of root-zone soil moisture in agricultural landscapes. One method is based on observing rainfall and dynamically updating a root-zone water balance model. The other two methods are based on thermal and microwave remote sensing techniques. As discussed in the paper, all three methods have their own individual strengths and weaknesses. Here, we develop and present a mathematical strategy for optimally integrating all three methodologies to produce an accurate a root-zone soil moisture estimate as possible. Preliminary results are based on a synthetic data analysis. These results are then supplement with real data collected from a long-term field site at BARC.
Technical Abstract: The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, the vertical support of microwave-based surface soil moisture retrievals (top 2 to 5 cm of the soil column) are generally considered too shallow for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that, if properly interpreted, can be used to define a robust proxy for soil moisture availability in the root zone (defined here as the top 1 meter of soil). In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model. Synthetic twin data assimilation results demonstrate that, despite the accuracy and temporal frequency limitations of thermal infrared soil moisture estimates, their inclusion into a dual assimilation problem can aid in the estimation of root-zone soil moisture. The degree of the improvement is shown to be contingent on soil hydraulic properties as well as the magnitude of vertical cross-correlation in soil moisture modeling errors at different soil depths. In addition to the synthetic analysis, preliminary real data results are also presented.