Soil moisture is an essential variable in hydrologic, land-surface and reactive transport processes. The intermediate-scale cosmic-ray soil moisture observing system (COSMOS) provides average soil water content measurement over a footprint of 0.34 km2 with depths up to 70 cm and an innovative means to understand watershed water dynamics. Compared with point measurements at the scale of centimeters, the COSMOS data represent averaged soil moisture at the scale of hundreds of meters. In this study, we test the use of COSMOS observations in constraining parameters in a physics-based hydrology model Flux-PIHM via the ensemble Kalman filter (EnKF). We aim to investigate 1) how COSMOS data can be used to predict soil moisture in a low-order watershed by Flux-PIHM, 2) which parameters are critical in predicting areal averaged soil moisture, and 3) how changes in data availability of the COSMOS influence prediction of watershed hydrodynamics. Synthetic data experiments are performed at the Shale Hills Susquehanna Critical Zone Observatory in central Pennsylvania. The COSMOS data is assimilated into Flux-PIHM using the EnKF, in addition to discharge and land surface temperature observations. The assimilation of COSMOS measurements can improve the model prediction of top layer soil moisture, and the soil parameters like van Genuchten β and porosity are critical in reproducing areal averaged soil moisture. The accuracy of EnKF estimated parameters and water and energy flux predictions is evaluated, reflecting the sensitivity of the observation to the corresponding parameter related hydrologic processes. In addition, the results are compared with assimilating point soil moisture measurement to assess the effects of soil moisture measurements at different scales in calibrating Flux-PIHM. The data retrieval frequency experiments evaluate the consequence of data availability on the hydrodynamics of simulated soil moisture profiles. We found that there exists an optimal data retrieval frequency where the calibrated model can be used to accurately predict watershed hydrodynamics.
Cai, Z., Xiao, D., Shi, Y., and Li, L. (2016): Assimilating the cosmic-ray soil moisture observing system measurements for understand watershed hydrodynamics. 2016 Fall Meeting, American Geophysical Union, San Francisco, CA, 12-16 Dec..
This Paper/Book acknowledges NSF CZO grant support.