Addressing rice yield gap during El Nino and La Nina events using DSSAT-CAMDT / Gerlie D. Sensano

UTHESIS (Bachelor of Science in Agricultural and Biosystems Engineering)

Bibliography: leaves 59-61

Rice production in the Philippines is critically impacted by climatic variability, particularly the extreme weather events associated with El Niño. This study employs the Decision Support System for Agrotechnology Transfer (DSSAT) and the Crop and Management Decision Tool (CAMDT) to develop and validate adaptive rice production management strategies. The objectives were to simulate rice crop responses under various El Niño scenarios using historical climate data, develop irrigation schedules and optimal planting dates, and recommend effective management practices to mitigate yield gaps. Simulated results indicate significant yield reductions under El Niño conditions, with the most severe impacts observed for late planting dates. Optimal planting dates were identified as June 11, July 26, and August 21 under El Niño scenarios, with corresponding yield improvements when compared to normal conditions. The study also developed targeted irrigation management schemes, adjusting irrigation timing and amounts based on the intensity of El Niño conditions. These interventions resulted in substantial yield improvements, particularly for late-planted crops, with increases ranging from 21.74% to 167.37%. The findings highlight the critical importance of early planting and precise irrigation management in mitigating the adverse effects of El Niño. These adaptive strategies are supported by extensive literature, which emphasizes the role of tailored management practices in enhancing crop resilience to climatic stress. The study provides a robust framework for optimizing rice production under El Niño conditions, contributing to improved food security and agricultural sustainability in the Philippines.