Browse data: Variable
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Type: Is input for: (Click arrow to add another value) Showing below up to 21 results in range #1 to #21.
- Bioenergy production (Total bioenergy production., type: model (from/to model))
- Crop irrigation water demand - grid (Water requirements for crop irrigation, calculated as daily moisture deficit during the growing season., type: model (from/to model))
- Crop production (Regional production per crop., type: model (from/to model))
- Demand for primary energy (Total demand for energy production. Sum of final energy demand and energy inputs into energy conversion processes., type: model (from/to model))
- Energy resources (Volume of energy resource per carrier, region and supply cost class (determines depletion dynamics)., type: driver)
- Grass requirement (Grass requirement; ruminants (nondairy cattle, dairy cattle, sheep and goats) are grazing animals, and part (in mixed systems) or most (pastoral systems) of their feed is grass, hay or other roughage; this grass requirement is calculated as a fraction of the total energy (feed) requirement., type: model (from/to model))
- Increase in irrigated area - grid (Increase in irrigated area, often based on external projections (e.g., FAO)., type: driver)
- Irrigation system (Type of irrigation system: surface, sprinkler or drip. This is allocated at country level, based on Jagermeyr et al (2015)., type: driver)
- Land cover, land use - grid (Multi-dimensional map describing all aspects of land cover and land use per grid cell, such as type of natural vegetation, crop and grass fraction, crop management, fertiliser and manure input, livestock density., type: model (from/to model))
- Land supply for bioenergy - grid (Land available for sustainable bioenergy production (abandoned agricultural land and non-forested land)., type: model (from/to model))
- Learning rate (Determines the rate of technology development in learning equations., type: driver)
- Management intensity crops (Management intensity crops, expressing actual yield level compared to potential yield. While potential yield is calculated for each grid cell, this parameter is expressed at the regional level. This parameter is based on data and exogenous assumptions - current practice and technological change in agriculture - and is endogenously adapted in the agro-economic model., type: model (from/to model))
- Population - grid (Number of people per gridcell (using downscaling)., type: driver)
- Potential bioenergy yield - grid (Potential yields of bioenergy crops., type: model (from/to model))
- Potential crop and grass yield - grid (Potential crop and grass yield, changing over time due to climate change and possibly soil degradation. In some components, i.e. 'Agricultural economy' regional aggregations of the dataset which depend on the actual land-use area, are used., type: model (from/to model))
- Precipitation - grid (Monthly total precipitation., type: model (from/to model))
- Protected area - grid (Map of protected nature areas, limiting use of this area., type: driver)
- River discharge - grid (Average flow of water through each grid cell., type: model (from/to model))
- Technology development of energy supply (Learning curves and exogenous learning that determine technology development., type: driver)
- Temperature - grid (Monthly average temperature., type: model (from/to model))
- Trade restriction (Trade tariffs and barriers limiting trade in energy carriers (in energy submodel)., type: driver)