Background
EPIC requires plot-scale data, where weather, soil, topography and crop management systems are assumed to be homogeneous. Therefore, the data (see above) has to be processed to delineate a global HRU layer This HRU concept assures consistency in integrating the biophysical impact vectors from EPIC in an economic land use optimization model (e.g. Global FASOM, GLOBIOM, BeWhere, etc.). A two-step hierarchical process has been developed to delineate the HRUs (Schmid et al., 2007): * In the first step, parameters of landscape are merged (e.g. altitude, slope, soil texture), which are relatively stable over time (even under climate change) and hardly affected by farm management. * In the second step, the HRU layer obtained in the first step is merged with land cover categories, weather, crop rotation and management, and boundary information to derive individual simulation units (ISU). Each ISU represents a certain share in a spatial unit, which is simulated with EPIC to deliver spatially and temporally explicit biophysical impact vectors. These ISUs along with their physical characteristics (crop yields, emissions) and their specific other attributes (area, management) are treated as an activity in economic land use optimization models. If all potential alternative ISUs are simulated with the biophysical process model then one can construct a production and / or emission possibility set that an economic land use optimization model can choose from.Data
data listed above.Methods
GIS.Results
The global HRU layer (see figure 2) has been constructed and combined with all relevant data to derive individual simulation units (ISU). Each ISU contains information on weather, soil, topography, land use, and crop management. Currently, we are working in construction spatially explicit crop rotations.
Figure 2: The global HRU layer