Impacts of El Niño Climate Anomaly on Irrigation Scheduling of Maize Crop Using Budget Models under Tropical Climate Conditions

Momon Sodik Imanudin, Bakri Bakri, Karimuddin Y, P. Ratmini


The research aims to calculate the water requirement and irrigation interval of maize crop as well as to design water-efficient irrigation application system. The study was conducted on dry land of Palembang city of South Sumatra. The indicator crop used in this study was maize. Daily climate data were taken from Sultan Mahmud Badarudin and Kenten station. The research applied survey method, laboratory analysis, computer simulation and irrigation design. The calculation of water crop deficiency was done using empirical approach by multiplying the potential evapotranspiration value by crop coefficient. Soil water retention characteristic was recorded based on the calculation of the length of water available to plants. Daily rainfall in the field was recorded as water input other than water from irrigation. The combination of soil, climate and plant physiological properties (Agro-pedo-climatic) will result in a water irrigation system in a region. Water balance analysis was developed by the help of computer model (BUDGET model). The result of computer model analysis shows that maize crop in rainy season does not require irrigation. While for the transition period (March-May), irrigation is required for the flowering phase with a total water requirement of 76.5 mm. During dry season (May-July), irrigation is required with water requirement of 198 mm. Irrigation scheduling is set up 9 times with intervals every 7 days at the beginning of growth and 10 days at the middle and end. While the testing under dry climate conditions (El Niño) using rainfall data in 2015 indicates irrigation should be given since March and during planting period (May-August 2015) the irrigation should be applied 12 times with intervals every 5 days at the initial stage and 10 days during vegetative stage.


Irrigation scheduling; Maize crop; Agropedoclimatic data; Budget model

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