A simplified approach to energy-water modeling for controlled environment agriculture

An increasingly implemented alternative to outdoor farming, controlled environment agriculture (CEA) ensures reliable food production despite volatile growing conditions such as drought, flooding, and extreme temperatures. CEA can bolster local food production and revenue, promoting food resilience; however, the high energy and, in some cases, water demands required to optimize indoor environments for crop growth are a notable barrier to adoption. Understanding the resource consumption of CEA facilities is crucial to the sustainable growth of this sector, but existing models tend to be computationally intensive, proprietary, or require detailed design data. To address this issue, we propose a simplified, flexible model (CEAEstA) that integrates fundamental lighting, heating, cooling, and evapotranspiration principles to estimate energy and water demand. The model is designed to be accessible for early-stage feasibility assessments, allowing stakeholders to evaluate sustainability trade-offs before committing to more detailed analyses. Leveraging both empirical and modeled datasets from peer-reviewed literature for validation, this study demonstrates the model’s effectiveness in estimating order-of-magnitude energy and water consumption across different facility types, crops, and climate zones. The results highlight the key drivers of resource demand in CEA and provide insights into designing efficient facilities and developing sustainable operational strategies.