Revealing trade-offs in cropping systems sustainability by piecing together pedo-climatic datasets and agronomic knowledge with fuzzy logic

摘要: Agriculture is among the sectors most affected by climate change and, simultaneously, is the primary responsible for anthropogenic non-CO2 greenhouse gas (GHG) emissions worldwide. Nonetheless, the actual estimation of global GHGs emissions due to agricultural activities is still subject to significant uncertainty. The Intergovernmental Panel on Climate Change (IPCC) and the Water Footprint Network (WFN) provide a set of equations and emission factors, the so-called Tier 1, for separately estimating carbon stock changes, N2O emissions, and NO3 leaching losses under a limited set of pedo-environmental conditions and agricultural Soil Management Strategies (SMS, ie, crop choice, fertilization, irrigation, and soil tillage). However, the Tier 1 methodologies do not explicitly consider the multi-faceted interactions among SMS, pedo-environmental variability, and nitrogen and carbon fluxes. Indeed, current …