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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Online vegetation opacity parameter estimation over Little Washita watershed using AMSR-E passive microwave observations

Authors
item Fitzmaurice, Jean
item Crow, Wade

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: January 15, 2012
Publication Date: January 21, 2012
Citation: Fitzmaurice, J.A., Crow, W.T. 2012. Online vegetation opacity parameter estimation over Little Washita watershed using AMSR-E passive microwave observations [abstract]. Meeting Abstract. 2012 CDROM.

Technical Abstract: The vegetation opacity parameter is a key input needed to map surface soil moisture and other landsurface properties to brightness temperature. An integrated approach to estimating vegetation and soil moisture may provide a better soil moisture estimate than relying on opacity estimates from visible/near infrared vegetation indices. We test a new online vegetation parameter estimation method using AMSR-E satellite observations over Little Washita watershed during several growing seasons. An ensemble Kalman filter consisting of a multi-layer soil hydrology model and an omega-tau type radiative transfer model is used to assimilate C-band and X-band, vertical and horizontal polarization observations. A state augmentation approach which appends the parameter(s) to the state vector is used for parameter estimation. Open loop filter statistics (without observation updates) and filter soil moisture statistics using AMSR-E data are computed using an in situ soil moisture dataset available starting from July 2002 in Little Washita watershed. Results show that vegetation parameter estimates are reasonable. Observation bias correction parameter estimation tests within the ensemble Kalman filter are also discussed. This research is relevant for applications directly assimilating brightness temperature observations such as the planned NASA SMAP (Soil Moisture Active Passive) Level 4 surface and root zone soil moisture product.

Last Modified: 7/23/2014
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