The fundamental principles of smart irrigation hinges upon precise assessments of soil moisture content within the root zone layer. Various techniques have been developed to ascertain root zone soil moisture content, such as using soil moisture measurement sensors or simulation models. Each one of these methods has its own distinct advantages and disadvantages. Data assimilation encompasses an array of approaches that combine model estimates with the corresponding observed data to derive a more precise estimations of the required data. The purpose of this research is to ascertain the feasibility of reducing the number of depths at which soil moisture measurements were taken and increasing the time interval between two consecutive soil moisture measurements using the Ensemble Kalman filter.

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