Publications in Scientific Journals:

H. Lievens, R. Reichle, Q. Liu, G. De Lannoy, R. Dunbar, S. Kim, N. Das, M. Cosh, J. Walker, W. Wagner:
"Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates";
Geophysical Research Letters, 44 (2017), 12; 6145 - 6153.

English abstract:
SMAP (Soil Moisture Active and Passive) radiometer observations at ∼40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model to generate the 9 km SMAP Level-4 Soil Moisture product. This study demonstrates that adding high-resolution radar observations from Sentinel-1 to the SMAP assimilation can increase the spatiotemporal accuracy of soil moisture estimates. Radar observations were assimilated either separately from or simultaneously with radiometer observations. Assimilation impact was assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to December 2016. The Sentinel-1 assimilation consistently improved surface soil moisture, whereas root-zone impacts were mostly neutral. Relatively larger improvements were obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performed best, demonstrating the complementary value of radar and radiometer observations.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.