An Initial Approximation to the Simulation of Soil CO2 Emissions Using the IPCC Methodology in Agricultural Systems of Villavicencio

Abstract

At a global level, the agricultural sector has represented the largest source of greenhouse gas (GHG) emissions. Our research hypothesizes whether it is possible to faithfully define the effect of soil management factors on modeling soil carbon organic (SOC) sequestration and reducing soil CO2 emissions in different agricultural systems across three zones of Villavicencio (Colombia) by applying the Tier-1 IPCC process‐based model. Agroforestry systems (AFS) are typically found in zone 1, and intensive croplands (CL) in zones 3 and 4. Soil CO2 emissions rates are calculated according to the current IPCC guidelines for national GHG inventories. Root-mean square error (RMSE, RMSE/n), R2, and Nash‐Sutcliffe efficiency (NSE) are measured to assess model performance. In zone 1, 7-year coffee-based agroforestry stored higher SOC, neutralizing -10,83t CO2 eq ha-1 year−1 than 25-year soybean/corn crop rotation in zone 3, with emissions of 2,56t CO2eq ha-1 year-1. The agricultural systems of zones 3 and 4 turned out to be greater emitters, with 7 223 and 3 889t CO2 eq year-1, respectively, which could increase if CL continues to adopt agricultural practices that encourage full tillage. The beneficial effects of AFS on stored SOC are identified via field observations and correctly reproduced by RMSE evaluation.