  Improving the accuracy of soil moisture estimation is desirable from the
perspectives of irrigation management and water conservation. To this end, this
study proposes a systematic approach to select a subset of soil hydraulic
parameters for estimation in large-scale agrohydrological systems to enhance
soil moisture estimation accuracy. The proposed method involves simultaneous
estimation of the selected parameters and the entire soil moisture distribution
of the field, taking into account soil heterogeneity and using soil moisture
observations obtained through microwave radiometers mounted on a center pivot
irrigation system. At its core, the proposed method models the field with the
cylindrical coordinate version of the Richards equation and addresses the issue
of parameter estimability (quantitative parameter identifiability) through the
sensitivity analysis and orthogonal projection approaches. Additionally, the
study assimilates remotely sensed soil moisture observations into the field
model using the extended Kalman filtering technique. The effectiveness of the
proposed methodology is demonstrated through numerical simulations and a real
field experiment, with cross-validation results showing a 24-43% improvement in
soil moisture estimation accuracy. Overall, the study highlights the potential
of this method to enhance soil moisture estimation in large-scale agricultural
fields.
