Agricultural Greenhouse Gas Emissions in a Data-Scarce Region Using a Scenario-Based Modeling Approach: A Case Study in Southeastern USA

Abstract

Climate change may impact agricultural greenhouse gas emissions (GHGs) and yields under higher temperatures, higher atmospheric CO2 concentrations, and variable precipitations. This calls for adaptation strategies to optimize agricultural productions with minimal GHGs. This study aimed to identify these optimum agricultural managements in response to current and projected climatic scenarios for the Choctawhatchee Basin in Southeastern USA, an experimentally unexplored data-scarce region lacking validation data. This scenario-based modeling study analyzed a total of 1344 scenarios consisting of four major crops, eight managements (varying tillage, manuring, and residue), and forty climatic combinations under current as wells as two representative concentration pathways with process-based Denitrification and Decomposition (DNDC) model. The results indicated that the region’s GHGs and yields were most affected by higher temperatures (≥+3 °C) and extreme precipitation changes (≥±40%), while high atmospheric CO2 concentrations exerted positive fertilization effects. The manure-related and higher residue incorporation scenarios were found to be better options in varying climates with minimal present global warming potentials (GWP) of 0.23 k to −29.1 k MT equivalent CO2. As such, the study presented climate change impacts and potential mitigation options in the study region while presenting a framework to design GHG mitigation in similar data-scarce regions.