A Data-Driven Intelligent Decision-Making Model for Irrigation Scheduling

Agriculture relies heavily on irrigation, but this essential practice consumes a significant portion of our increasingly scarce freshwater resources. Climate change and urban expansion exacerbate this challenge, making efficient irrigation management a critical factor in global sustainability. Additionally, excessive irrigation harms the environment by polluting waterways, depleting water sources, and salinizing soil. This webinar presents a groundbreaking data-driven intelligent irrigation scheduling model that optimizes water use efficiency and promotes agricultural sustainability. By leveraging readily available soil moisture and evapotranspiration data from the High-Resolution Land Data Assimilation System (HRLDAS), the model provides precise irrigation recommendations tailored to specific field conditions. Key benefits of the decision model include: – 20-40% water savings: Achieve significant water conservation while ensuring optimal crop growth. – Increased crop yield: Maximize production by providing the right amount of water at the right time. – Reduced environmental impact: Minimize water pollution and soil salinization for a healthier environment. – Cost-effective and easy to implement: No expensive sensors or data subscriptions required, making it accessible to all farmers. During this webinar, you will learn the decision support system in depth: – How the data-driven model works and its key features – The benefits of ET-Water Balance and soil-moisture based irrigation scheduling methods. – How deep reinforcement learning further optimizes irrigation decisions. – Real-world examples and case studies showcasing the model’s effectiveness. – How to access and utilize the model through the free WaterSmart Data Information Portal. Speaker(s): Haoteng Zhao, Virtual: https://events.vtools.ieee.org/m/389291