Open AccessEstimating Greenhouse Gas Emissions from Irrigated Paddy Fields in Indonesia under Various Water Managements
Author(s) -
Chusnul Arif,
Budi Indra Setiawan,
Nur Aini Iswati Hasanah,
Masahiro Mizoguchi
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/557/1/012034
Subject(s) - greenhouse gas , paddy field , environmental science , nitrous oxide , methane , greenhouse , environmental engineering , hydrology (agriculture) , soil science , agronomy , chemistry , ecology , geology , geotechnical engineering , organic chemistry , biology
Methane (CH 4 ) and nitrous oxide (N 2 O) are two main greenhouse gasses emitted from paddy irrigated paddy fields. Their fluxes are commonly affected by water managements in the fields. However, the main problem in the study of greenhouse gas emissions in paddy fields is the instrumentation for measuring emissions. Measurements of greenhouse gas emissions are costly and complicated. The current study proposes estimating method to quantify greenhouse gas emissions by an artificial neural network (ANN) model. They are estimated based on easily measurable parameters such as soil moisture, soil temperature, soil electrical conductivity (EC), soil redox potential (Eh) and soil pH. The model was verified based on field experiments that were conducted in Bogor, West Java, Indonesia during 26 March – 24 June 2015. Here, three regimes of water management, i.e. continuous flooded (FL), moderate (MR) and dry (DR) regimes, were performed in the field. The DR regime released the lowest total greenhouse gas emissions; however, it reduced grain yield by 58% and 12% compared to the FL and MR regimes respectively. The developed model showed high accuracies for both greenhouse gasses estimation where the coefficients of determination (R 2 ) values were 0.84 and 0.76 for CH 4 and N 2 O prediction respectively.