Tuesday, 9 January 2018: 11:30 AM
Room 4ABC (ACC) (Austin, Texas)
Data assimilation has enjoyed widespread applications in weather forecasting and hydrology. Its use in disciplines such as biogeochemistry however is rather limited. In this talk I will discuss opportunities in the field of hydrology and biogeochemistry for the use of Ensemble-based Simultaneous State and Parameter Estimation (ESSPE), A Generalized Data Assimilation Software Infrastructure for Earth System Data-Model Integration and Uncertainty Quantification. The rapid advances in technology and the generation of novel data have enabled the collection of novel hydrobiogeochemcal data in coordinated efforts through various research communities at scales as small as nanometers to those as large as the globe. The use of ESSPE will allow identification of key parameters and critical measurements, quantification of model uncertainties, and facilitation of observation system design. In this talk we will show the use of ESSPE through the ensemble Kalman filter (EnKF) in assimilating a new type of soil moisture data from the intermediatescale cosmicray soil moisture observing system (COSMOS). Compared with point measurements at the centimeter scale such as the time-domain reflectometry (TDR), the COSMOS data represent averaged soil moisture at hundreds of meters. The COSMOS data are assimilated into the land surface hydrologic model FluxPIHM in addition to discharge and land surface temperature observations in a synthetic experiment. We found that the assimilation of COSMOS measurements can improve the model prediction of top layer soil moisture and constrain soil hydraulic parameters including van Genuchten β and porosity. It however cannot constrain all soil hydraulic parameters if used alone. The combination of COSMOS, discharge, and TDR data are important in estimating soil water retention capability related parameters. The TDR is more effective to constrain the soil parameters, which is consistent with the smaller duration time of rain-runoff response presented by TDR observations.
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