Author
|
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 7/8/2013 Publication Date: 11/3/2013 Citation: Crow, W.T. 2013. Constraining root-zone soil water availability using data assimilation and satellite remote sensing [abstract]. Proceeeding of the 2013 American Society of Agronomy Meeting, November 3-6, 2013, Tampa, Florida. 2013 CDROM. Interpretive Summary: Technical Abstract: Large-scale monitoring of root-zone soil water availability, and therefore the duration and extent of regional agricultural drought, has emerged as an important application for satellite remote sensing and figures heavily into plans for next-generation earth observing satellites. At present, three globally-scalable strategies exist for monitoring root-zone soil moisture availability: 1) forcing a prognostic soil water balance model using satellite-based precipitation products, 2) vertical extrapolating surface (0 to 5-cm) soil moisture retrievals obtained by satellite-based microwave sensors, and 3) inverting variations in surface radiometric temperature (as measured by satellite-based thermal infrared sensors) to infer the onset of vegetative water stress. In addition to these three methods applied in isolation, a range of data assimilation strategies exist for integrating diagnostic satellite-based retrievals (obtained from methods #2 and #3) into prognostic water balance modeling approaches (method #1). Such data assimilation methods are particularly important for the integration of microwave-based observations, as the 1-dimensional physics of the water balance model can provide a physically-realistic constraint for vertically extrapolating surface soil moisture retrievals into root-zone estimates required for ecological/agricultural forecasting applications. This talk will briefly review the state-of-the-art in all three of the methods listed above and describe their potential as the basis for a large-scale agricultural drought monitoring system designed for the early detection of drought impacts on agricultural productivity. Particular emphasis will be paid to describing prospects for designing data assimilation systems to simultaneously integrate soil moisture information derived from both thermal and microwave remote sensing sources into water balance modeling approaches. Such integrative systems offer the potential to compensate for unique deficiencies found in all three available sources of root-zone soil moisture information. |
