|Han, Eunjin -|
|Merwade, Venkatesh -|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: May 21, 2010
Publication Date: May 26, 2010
Citation: Han, E., Heathman, G.C., Merwade, V. 2010. Calibration of the Root Zone Water Quality Model and Application of Data Assimilation Techniques to Estimate Profile Soil Moisture [abstract]. Indiana Water Resources association Spring Meeting, Indiana Waters: emergin Wters, emerging C ontaminants, Emergin Communities, May 26-28, 2010, West Lafayette, Indiana. CD ROM. Technical Abstract: Estimation of soil moisture has received considerable attention in the areas of hydrology, agriculture, meteorology and environmental studies because of its role in the partitioning water and energy at the land surface. In this study, the USDA, Agricultural Research Service, Root Zone Water Quality Model (RZWQM) was used to simulate profile soil moisture in two agricultural fields in northern Indiana. First, the model was calibrated for measured runoff and soil moisture content by adjusting soil hydraulic properties, soil macroporosity and tile drainage parameters. Second, the model simulation results were updated by applying two data assimilation techniques: Ensemble Kalman Filter (EnKF), and direct insertion method. This updated step was based on the assumption that assimilating measured 5cm surface soil moisture, such as remotely sensed data, into hydrologic modeling would produce better estimates of soil water content in the entire profile. Among the measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm), only the top 5cm data were assimilated on a daily basis and the simulated results were validated using all of the measured data. Overall, the results of this study indicate that daily (or bi-daily) assimilation of surface soil moisture improves soil moisture estimation in the upper more dynamic layers (5 and 20cm) but has less affect at deeper layers (40 and 60cm).