Modeling Evapotranspiration and Yield Components of Cotton under Deficit Irrigation in Arid Zones

Abstract

The increasing scarcity of water resources in arid regions has necessitated the development of efficient irrigation strategies to sustain crop productivity. This study focuses on modeling evapotranspiration and yield components of cotton under deficit irrigation in arid zones to optimize water use and maintain yield performance. The proposed methodology integrates field experimental data with data-driven and analytical modeling techniques. Multi-source datasets, including climatic variables (temperature, humidity, solar radiation, and wind speed), soil moisture levels, irrigation treatments, and crop growth parameters, are collected and preprocessed through cleaning, normalization, and feature engineering to ensure consistency and reliability. Advanced modeling approaches, including regression analysis, Random Forest, and Artificial Neural Networks, are employed to estimate evapotranspiration rates and evaluate their relationship with yield components such as boll number, boll weight, and biomass production. The system is trained and validated using region-specific datasets to ensure adaptability under arid environmental conditions. Experimental results demonstrate that deficit irrigation strategies significantly reduce water consumption while maintaining acceptable yield levels when applied at critical growth stages. The modeling framework accurately predicts evapotranspiration dynamics and identifies optimal irrigation regimes that balance water savings with yield stability. Additionally, improved water use efficiency and resource optimization are observed compared to conventional full irrigation practices. The findings highlight the effectiveness of combining artificial intelligence with evapotranspiration modeling for precision agriculture in water-limited environments. The study concludes that intelligent modeling of evapotranspiration and yield components under deficit irrigation provides a scalable and sustainable solution for enhancing cotton productivity and water management in arid regions.