Comparison of SMOS vegetation optical thickness data with the proposed SMAP algorithm

Soil moisture is important to agriculture, weather, and climate. Current soil moisture networks measure at single points, while large spatial averages are needed for some crop, weather, and climate models. Large spatial average soil moisture can be measured by microwave satellites. Two missions, the European Space Agency's Soil Moisture Ocean Salinity mission (SMOS) and NASA's Soil Moisture Active Passive mission (SMAP), can or will measure L-band microwave radiation, which can see through denser vegetation and deeper in to the soil than previous missions that used X-band or C-band measurements. Both SMOS and SMAP require knowledge of vegetation optical thickness (tau) to retrieve soil moisture. SMOS is able to measure tau directly through multi-angular measurements. SMAP, which will measure at a single incidence angle, requires an outside source of tau data. The current SMAP baseline algorithm will use a climatology of optical vegetation measurements, the normalized difference vegetation index (NDVI), to estimate tau. SMAP will convert the NDVI climatology to vegetation water content (VWC), then convert VWC to tau through the b parameter. This dissertation aimed to validate SMOS tau using county crop yield estimates in Iowa. SMOS tau was found to be noisy while still having a clear response to vegetation. Counties with higher yields had higher increases in tau; over growing seasons, so it appears that SMOS tau is valid during the growing season. However, SMOS tau had odd behavior outside of growing seasons which can be attributed to soil tillage and residue management. Next, this dissertation attempted to estimate values of the b parameter at the satellite scale using SMOS tau data, county crop yields, and allometric relationships, such as harvest index. A new allometric relationship was defined, thetagv,max, which is the ratio of maximum VWC to maximum dry biomass. While uncertainty in the estimated values of b was large, the values were close in magnitude to those found in literature for field-based studies. Finally, this dissertation compared SMOS tau to tau from SMAP's NDVI-based algorithm. At the peak of the growing season, SMAP tau was similar in timing to SMOS tau, while SMAP tau was larger in magnitude than SMOS tau. The larger SMAP tau could be attributed to SMAP's handling of vegetation scattering in its soil moisture retrieval algorithm. For one example case, the difference between SMAP tau and SMOS tau at the peak of the growing season did not appear to cause a large difference in retrieved soil moisture.