Assessment of Emissions with Carbon-smart Farming Practices and Participatory Sensing in Rice

Abstract

Agriculture sector is a significant contributor to greenhouse gas (GHG) emissions especially in the conventional rice ecosystem with carbon-insensitive practices. In this study, we assess the carbon footprint of selected farms based on GHG emissions and carbon sequestration from recommended agricultural practices with a human participatory sensing approach. A set of ten selected farmers was split into two groups and asked to follow carbon-smart crop protocols (CSCP) called CSCP-1 and CSCP-2. With the digitally captured record of operations, process modelling was used to simulate the CSCP scenarios followed on the ground, and a classification model was developed to estimate the Nitrogen uptake to improve fertilizer utilization for farmers. For various potential scenarios involving variation in irrigation and fertilizer application, impact on GHG emissions and SOC dynamics was evaluated. Results showed that CSCP-1 farmers emitted more GHGs when compared to CSCP-2 farmers while they also sequestrated more carbon in comparison with no significant difference in Net GWP (Global Warming Potential). CSCP farmers with both flood irrigation and furrow irrigation sequestrated more carbon than farmers who would follow conventional practices. Net GWP of CSCP farmers was significantly lower than conventional farmers indicating carbon-smart practices can indeed make a significant difference in sustainability initiatives.