Modeling Crop Coefficient and Water Requirement of Banana under Micro-Irrigation

Abstract

The efficient estimation of crop water requirements is essential for optimizing irrigation practices and enhancing water use efficiency in high-value crops such as banana. This study focuses on modeling the crop coefficient and water requirement of banana under micro-irrigation systems to support precise irrigation management. The proposed methodology integrates field experimental observations with data-driven and analytical modeling approaches. Multi-source datasets, including climatic variables (temperature, humidity, solar radiation, and wind speed), soil moisture levels, and crop growth parameters across different phenological stages, are collected and preprocessed through cleaning, normalization, and feature engineering techniques to ensure data reliability. The crop coefficient (Kc) values are estimated using evapotranspiration data and validated through lysimeter measurements and sensor-based observations. Advanced machine learning models, including regression techniques, Random Forest, and Artificial Neural Networks, are employed to capture nonlinear relationships between environmental variables and crop water requirements. The system is trained and validated using region-specific datasets to ensure robustness across varying agro-climatic conditions. Experimental results indicate that micro-irrigation significantly improves water use efficiency and enables precise control of water application throughout different growth stages of banana. The developed models accurately predict crop coefficient values and irrigation requirements, reducing water wastage while maintaining optimal plant growth and yield. Additionally, stage-wise variation in Kc values provides insights for efficient irrigation scheduling. The findings highlight the effectiveness of integrating artificial intelligence with crop coefficient modeling for precision agriculture applications. The study concludes that smart modeling of crop water requirements under micro-irrigation offers a scalable, efficient, and sustainable solution for optimizing water management and improving banana productivity.