• Corpus ID: 62828826

1 Joint State and Parameter Estimation of Two Land Surface Models Using the Ensemble Kalman Filter and Particle Filter

@inproceedings{Zhang20161JS,
  title={1 Joint State and Parameter Estimation of Two Land Surface Models Using the Ensemble Kalman Filter and Particle Filter},
  author={Hongjuan Zhang and Harrie-Jan Hendricks-Franssen and Xujun Han and Jasper A. Vrugt and Harry and Vereecken},
  year={2016}
}
Land surface models (LSMs) contain a suite of different parameters and state variables to resolve the water and energy balance at the soil-atmosphere interface. Many of the parameters of these models cannot be measured directly in the field, and require calibration against flux and soil moisture data. In this paper, we use the Variable Infiltration Capacity Hydrologic Model (VIC) and the Community Land Model (CLM) to simulate temporal variations in soil moisture content at 5, 20 and 50 cm depth… 

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