Abstract
The Richards’ equation is widely used in the modeling soil water dynamics driven by the capillary and gravitational forces in the vadose zone. Its state and parameter estimation based on field soil moisture measurements is important and challenging for field applications of the Richards’ equation. In this work, we consider simultaneous state and parameter estimation of systems described by the three dimensional Richards’ equation with multiple types of soil. Based on a study on the interaction between subsystems, we propose to use decentralized estimation schemes to reduce the complexity of the estimation problem. Guidelines for subsystem decomposition are discussed and a decentralized estimation scheme developed in the framework of moving horizon state estimation is proposed. Extensive simulation results are presented to show the performance of the proposed decentralized approach.
Highlights
Agriculture accounts for about 70% consumed fresh water according to the United Nations statistics [1]
If we examine the current irrigation practice from a systems engineering perspective, majority of irrigation currently is done in an open-loop manner, in which no real-time field measurement is used in irrigation decision making
We focus on infiltration processes that can be described by the Richards’
Summary
Agriculture accounts for about 70% consumed fresh water according to the United Nations statistics [1]. The average water-use efficiency in agriculture irrigation is about 50%. In order to achieve water sustainability, it is important to significantly improve the water-use efficiency in agriculture irrigation. Closed-loop irrigation, in which real-time field measurements are used to determine the time and the amount of water to be applied, is a promising alternative to significantly reduce water consumption. In the implementation of a closed-loop irrigation system, the soil moisture information of the entire field is important. It is, very expensive to install sufficient number of sensors to cover one agriculture field. One approach to conquer this challenge is to use a model of the field and state estimate to reconstruct the soil moisture of the entire field based on the measurements of a small number of sensors. We focus on infiltration processes that can be described by the Richards’
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