Droughts can seriously suppress crop growth and reduce yields, threatening food production worldwide. Detecting and understanding drought effects are essential for managing crops and ensuring food security. Traditional ways of monitoring crops are time-consuming and labor-intensive and often miss subtle signs of drought. In this study, we develop an scalable and integrated approach for drought monitoring and water use characterization by integrating UAV-based advanced sensors and multimodal artificial intelligence. By combining UAV data and ground-based plant and soil measurements, this study offers insights into how corn plants use water and interact with drought. Our approach helps improve drought detection and could guide farmers and agricultural specialists in making better informed decisions to protect their crops under changing and pressing climate conditions.