Agent-based model predictive control of soil–crop irrigation with topographical information

Abstract

The amount of water in the soil has an impact on how well plants absorb nutrients. As a result, both above and below-the-surface water dynamics have an effect on crop growth. The quality of the soil and its mechanical qualities can be significantly altered by both an excess or a lack of water, which could make food production unsustainable. This study deals with the development of a precision farming approach to irrigation that considers the topographical features of the arable land and incorporates its morphological properties. The prediction of the water movement in the topsoil layer is an essential element of this strategy, which uses an agent-based model to describe the soil dynamics and the impact of irrigation and exploits a model predictive control (MPC) to optimize water usage. As a case study, the municipality of Samacá in the department of Boyacá, Colombia, is considered.