Impact of Spatial Resolution of SMAP Soil Moisture Product on Hydrologic Modeling of Soil Moisture
Abstract
Surface soil moisture is an important hydrologic state affecting land-atmosphere interactions, and is sensitive to climatic conditions, vegetation cover and soil properties. In this study, we evaluate the impacts of assimilating remotely sensed Soil Moisture Active Passive (SMAP) products at different spatial resolutions on the soil moisture simulations of a distributed hydrologic model, PAWS (Processed-based Adaptive Watershed Simulator). PAWS is used to simulate the surface (top 5-cm) soil moisture in a calibrated watershed model at a resolution of 1 km. SMAP products with different resolutions, e.g., 3-, 9- and 36-km are assimilated in PAWS using the Ensemble Kalman filter (EnKF). In-situ soil moisture observations from a network of TDR probes are compared with model outputs to evaluate the impacts of data assimilation of SMAP soil moisture at different spatial resolutions. Our results are expected to aid in understanding model improvements that result from the use of radiometer-only measurements of the SMAP mission relative to radar + radiometer observations from the same mission.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.H31G1480Q
- Keywords:
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- 1833 Hydroclimatology;
- HYDROLOGYDE: 1843 Land/atmosphere interactions;
- HYDROLOGYDE: 1855 Remote sensing;
- HYDROLOGYDE: 1866 Soil moisture;
- HYDROLOGY