Model Denitrification Decomposition (DNDC) Untuk Estimasi Emisi Gas Ch4 Pada Budidaya Padi Metode System of Rice Intensification (SRI) - Nihayah, Badi’atun; Nugroho, Bayu Dwi Apri; Hasanah, Nur Aini Iswati (Badan Perencanaan Pembangunan Daerah Kabupaten Bantul, 2021)
Rice cultivation is the main emission source in the agricultural sector, contributes to greenhouse gases, especially CH4. Reduction efforts CH4 gas emissions in this study carries out by integrating technological components among varieties, fertilizers, and intermittent irrigation through the cultivation of the System of Rice Intensification (SRI) method. This study aims to determine the effect of varieties and fertilization on CH4 gas emissions during one growing season and model CH4 emissions. Denitrification-Decomposition (DNDC) model predicts greenhouse gas emissions, which is CH4 from agricultural ecosystems. It uses a Nested Design with two treatment factors, namely fertilization consisting of manure and MOL (P1) and manure, ZA, SP36, and KCl (P2), and the various treatment, Ciherang (C) and IR-64 (IR). Results of observations showed the highest total CH4 emission was in the P1-IR treatment of 136.36 kg/ha/season, and the lowest was the P2-IR treatment of 88.09 kg/ha/season. Simulation results using DNDC also showed the P1-IR treatment produced the highest total CH4 emissions of 143 kg/ha/season, and the lowest was P2-IR treatment of 59 kg/ha/season. Evaluation of DNDC observation and simulation model for average daily CH4 flux with R2 and RMSE values ​​for each treatment, namely P1-C; P1-IR ; P2-C and P2-IR respectively (R2 = 0.65 ; RMSE = 13.19) ; (R2 = 0.003 ; RMSE = 3.55) ; (R2 = 0.17 ; RMSE = 32.06) and (R2 = 0.35 ; RMSE = 12.25). Results of the DNDC simulation still require optimization for the estimation of CH4 emissions at different fertilization and varieties.