Integration of inundation and soil moisture estimates in an ecosystem-atmosphere gas exchange model: Sensitivity and error analyses

John Galantowicz, AER, Inc., johng@aer.com (Presenter)
Arindam Samanta, Atmospheric and Environmental Research Inc., asamanta@aer.com
Hanqin Tian, Auburn University, tianhan@auburn.edu

Accurate estimation of seasonal and inter-annual changes in inundation, soil moisture, and wetland extent is a key requisite for the estimation of greenhouse gas (GHG) emissions from land surfaces to the atmosphere. In this study, we investigate how inundation and soil moisture data from NASA's Soil Moisture Active-Passive (SMAP) mission can be integrated into an ecosystem-atmosphere gas exchange model. SMAP, to be launched in 2014, will combine 1- to 3-km resolution synthetic aperture radar (SAR), 40-km-resolution L-band radiometry, and 3-day revisit period to make a novel dataset that can provide frequent inundation and soil moisture data. We plan to integrate these data with the Dynamic Land Surface Ecosystem Model (DLEM). DLEM quantifies regional fluxes of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) given atmospheric forcing data, with soil saturation as a prognostic variable. The combined SMAP-DLEM model will include a dynamic land cover fraction scheme such that soil moisture, inundation, and wetlands extent can be prescribed daily from remote sensing observation. In this poster we present results of two studies analyzing (1) the sensitivity of DLEM fluxes to inundation (i.e., soil saturation) and (2) SMAP inundation mapping capabilities. First, we evaluate DLEM model results for North America with normal and low/high precipitation anomalies to understand how the model would respond to SMAP-derived soil moisture and inundation inputs and how sensitive the response would be to retrieval errors. Second, we assess SMAP inundation mapping capabilities using a semi-empirical inundation retrieval algorithm and scene simulations based on the Phased Array L-Band Synthetic Aperture Radar (PALSAR) instrument onboard Japan’s Earth Resources Satellite’s (JERS). Results include predicted SMAP flooded-fraction (FF) retrieval errors stratified by resolution (3- to 10-km), land cover type, and FF category (0-1). We discuss implications of these results for formulation of a SMAP-DLEM data-model interface.

Presentation: 2011_Poster_Galantowicz_26_215.pdf (653k)

Presentation Type:  Poster

Session:  Coupled Processes at Land-Atmosphere-Ocean Interfaces   (Mon 4:00 PM)

Associated Project(s): 

• Galantowicz, John: Use of SMAP Seasonal Inundation and Soil Moisture Estimates in the Quantification of Global Biogenic Gas Fluxes ...details

Poster Location ID: 26