Soil Moisture Data Assimulation
Data Assimulation is a common approach used to combine the noisy observation with a propagation model for higher accuracy. Here we are using the level 2 soil moisture measurment from CYGNSS satellite with HYDRUS model to generate soil moisture estimation. Ensumble Kalman Filter is implement for the assimulation.
01
CYGNSS Observation
CYGNSS is a satellite constellation consisting of 8 satellites with GNSS-R receiver measurement on board. While over land surface, the reflected GNSS signal is gensitive to the soil moisture level at the specular reflection location.
02
HYDRUS Modeling
HYDRUS 1-D is used as the model for propagating the soil moisture over time. It is a FEA analysis of the water head over depth and take in the account of gravametric water movement, evaporation and vegetation root water uptake.
03
Ensumble Kalman Filter
Because the HYDRUS is a blackbox model, the covariance propagation is unknown, thus ensumble Kalman Filter is used. A ensumble is generated based on the input distribution and propagated through the model. The covariance is then calculated based on the out put of the ensumble.