Integrated Model Clusters

The models GLOBIOM, EPIC, G4M and POLES have been used for a long time in an integrated modeling framework at IIASA (see figure 1). 

EPIC (Izaurralde et al. 2006) supplies to GLOBIOM detailed information on management-related yields according to fertilizer and irrigation rates. EPIC is set up globally for 20 crops (barley, dry beans, cassava, chickpea, corn, cotton, cowpea, ground nuts, millet, oats, potatoes, rapeseed, rice, rye, soybeans, sorghum, sugarcane, sunflower, sweet potatoes and wheat). Four management systems are simulated by EPIC and implemented in GLOBIOM (irrigated, high input – rainfed, low input – rainfed and subsistence management systems). For each management system, EPIC provides to GLOBIOM information about yield, fertilizer and water requirements, as well as various environmental parameters including carbon and nutrient balance, and the connected greenhouse gas emissions, nitrogen leaching, soil erosion and other biophysical indicators (Table 1).

On the forestry sector side, G4M (Kindermann 2008) supplies to GLOBIOM information on mean annual increment, maximum share of biomass usable as saw logs in the mean annual increment, and harvesting costs. G4M also supplies to GLOBIOM consistent accounts of carbon stocks in forests which are then used to assess GHG emissions related to deforestation. In an iterative procedure, G4M uses in return GLOBIOM projections on wood, land and agricultural commodity prices and wood demand quantities, to estimate consistently future forest dynamics at high spatial resolution.

Additionally, GLOBIOM is linked to the JRC global energy model POLES (Prospective Outlook for the Long-term Energy System; Russ et al. 2007) through information on macroeconomic indicators and bioenergy demand. Bioenergy demand is split in first generation biofuels, second generation biofuels, bioenergy plants and direct biomass use for energy. Population and GDP projections from the POLES model are also used as exogenous drivers for the G4M baseline.

The economic model GLOBIOM (Havlík et al. 2011) bases its crop and forest sector details on biophysical parameters supplied by the more specialized models G4M (forestry) and EPIC (agriculture).

Last edited: 11 June 2012