Dynamic model reduction and optimal sensor placement for agro-hydrological systems

Abstract

One of the essential aspects of developing advanced closed-loop irrigation is the estimation of soil moisture from a limited number of available sensors. One of the challenges is to find the optimal location of the sensors in a large heterogeneous field. In this work, we propose a method to find the optimal location of sensors in the presence of heterogeneous soil and non-uniform inputs. The key steps include dynamic order model reduction, minimum sensor selection, optimal sensor placement, and state estimation. The proposed method is applied to a three-dimensional field through simulations, and satisfying model reduction and state estimation results are obtained.