Improving Soil Moisture States in WRF-Hydro Using SWOT Observations

The Surface Water Ocean Topography (SWOT) mission, launching in 2021, will provide high-spatial resolution measurements of terrestrial surface water, including global rivers with widths greater than 50-100 m. SWOT measurements are naturally suited for stream hydrology, and many previous studies have worked to quantify the impact of SWOT observations on the modeling of channel flow. However, SWOT measurements may also be useful in updating land surface states through data assimilation, although the use of SWOT measurements for these applications has not been widely investigated. To quantify the impact of SWOT measurements on land surface models, this work assimilates synthetic SWOT observations into the Weather Research and Forecasting Hydrological extension package (WRF-Hydro) to update soil moisture states for an Alaskan domain. WRF-Hydro was chosen since it is the foundation of the operational NOAA National Water Model. WRF-Hydro was configured with a 1-km resolution Noah-Multiparameterization Land Surface Model (Noah-MP LSM). Synthetic SWOT observations were derived from the SWOT Hydrology Simulator within a fraternal twin experiment, in which channel head output from a 100-m resolution WRF-Hydro simulation is used as the input Digital Elevation Map for the simulator. The synthetic SWOT observations were assimilated into a 250-m resolution WRF-Hydro simulation. These experiments used Global Land Data Assimilation System (GLDAS) meteorological forcing, which was regridded to match the 1-km resolution of the Noah-MP LSM. Results were validated using in situ measurements obtained from the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS).