Precision Irrigation for Agriculture

Precision Irrigation for Agriculture, 1st Edition, integrates machine learning, optimal control theory, and agricultural water management to design irrigation schedulers for large-scale agricultural fields. Authors Bernard Twum Agyeman and Jinfeng Liu introduce computational strategies tailored for field-scale water distribution.

The text addresses core aspects of soil moisture modeling. Specific covered subjects include soil water content, the energy status of soil water, the soil water retention curve, Darcy's law, and the Richards' equation. In addition, the volume presents methods for parameter selection and state estimation, outlining sensitivity analysis, the orthogonal projection method, and extended Kalman filter techniques.

This volume provides technical material for academic and professional readers who study or implement automated irrigation systems. The text supports researchers in process control, irrigation management specialists, field practitioners, and university students focusing on agriculture, water management, machine learning, and optimal control.