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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #294082

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Effect of forward/inverse model asymmetries over retrieved soil moisture assessed with an OSSE for the Aquarius/SAC-D

item Bruscantini, C
item Perna, P
item Ferrazoli, P
item Gringis, F
item Karszenbaum, H
item Crow, Wade

Submitted to: Journal of Applied Remote Sensing (JARS)
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/5/2013
Publication Date: 1/17/2014
Publication URL:
Citation: Bruscantini, C., Perna, P., Ferrazoli, P., Gringis, F., Karszenbaum, H., Crow, W.T. 2014. Effect of forward/inverse model asymmetries over retrieved soil moisture assessed with an OSSE for the Aquarius/SAC-D. Journal of Applied Remote Sensing (JARS). 50(1):371-375.

Interpretive Summary: Remotely-sensed surface soil moisture retrievals have the potential to contribute to a wide range of important agricultural applications including: fertilizer application, drought monitoring, yield forecasting, and irrigation scheduling. However, the value of current satellite-based soil moisture products is reduced by relatively high amounts of error in these retrievals - especially under dense vegetation canopies. Observing System Simulation Experiments (OSSEs) are powerful tools for examining - and potentially addressing - error sources that exist in current and future satellite data products. This paper describes the application of an OSSE to soil moisture products derived from the NASA Aquarius satellite mission. This particular OSSE examines strategies for improving Aquarius soil moisture retrievals within densely-vegetated landscapes. Eventually, the results obtained may allow us to do a better job measuring the amout of soil moisture present under closed agricultural crop canopies. This, in turn, will maximize the utility of satellite-based soil moisture retreivals for the key agricultural applications listed above.

Technical Abstract: An Observing System Simulation Experiment (OSSE) for the Aquarius/SAC-D mission that includes different models for forward and retrieval processes is presented. This OSSE is implemented to study the errors related to the use of simple retrieval models in passive microwave applications. To this end, a theoretical forward model was introduced, which is suitable to reproduce some of the complexities related to canopy vegetation scattering. So far, this OSSE has been successfully exploited to study the artifacts in the retrieved soil moisture associated to: (1) uncertainties and aggregation of the ancillary parameters needed for the retrieval and (2) instrumental noise effects. In this paper, we attempt to model the influence of this “model asymmetry” in the estimated soil moisture. These asymmetries are related to the fact that the emissivity of real surfaces is complex and strongly dependent on land cover type and condition. In particular, surface covered by average to dense vegetation presents complex scattering properties, related to canopy structure. Using this theoretical model, the difficulties related to retrieving soil moisture from passive data with a simple model are studied. The accuracy of the soil moisture estimation is analyzed in order to illustrate the impact of discrepancies between both models. In general, retrieved soil moisture performs worse over densely vegetated areas and under wet conditions. Furthermore, accuracy is highly dependent on land cover.