Penerapan Algoritma Genetika Untuk Optimasi Pengelolaan Air Lahan Padi Sawah Rendah Emisi Gas Metana (CH4)

Conventional paddy field with continuous flooding irrigation produces a lot of greenhouse gases (GHG) emissions, especially methane gas (CH4). Effective water management is important to reduce methane gas emissions from paddy fields. This study aimed to determine optimum water level and soil moisture in each plant growth stage by genetic algorithms (GA) with system of rice intensification (SRI) practices. Research was conducted with three irrigation regimes i.e, continuous flooding regime (FR), moderate regime (MR), and dry regime (DR). Observation data were used to simulate the optimum water level and soil moisture. Based on the optimum water level scenario of the GA model, methane gas emissions could reduce 63.54% and optimum soil moisture can reduce methane gas emission up to 58.12%.