Irrigation System Control With Predictive Water Balance Capabilities

Abstract

Disclosed are various embodiments for reinforcement learning-based irrigation control to maintain or increase a crop yield or reduce water use. A computing device may be configured to determine an optimal irrigation schedule for a crop planted in a field by applying reinforcement learning (RL), where, for a given state of a total soil moisture, the computing device performs an action, the action comprising waiting or irrigating crop. An immediate reward may be assigned to a state-action pair, the state-action pair comprising the given state of the total soil moisture and the action performed. The computing device may instruct an irrigation system to apply irrigation to at least one crop in accordance with the optimal irrigation schedule determined, where the optimal irrigation schedule includes an amount of water to be applied at a predetermined time.