Browse data: Variable

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Showing below up to 16 results in range #1 to #16.

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  • Crop irrigation water demand - grid (Water requirements for crop irrigation, calculated as daily moisture deficit during the growing season., 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)
  • 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 suitability - grid (Suitability of land in a grid cell for agriculture and forestry, as a function of accessibility, population density, slope and potential crop yields., 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))
  • Land systems - grid (Thirty land systems as defined in CLUMondo, characterized by specific levels of built-up area, cropland area, livestock density and management intensity., type: model (from/to model))
  • Learning rate (Determines the rate of technology development in learning equations., type: driver)
  • Potential bioenergy yield - grid (Potential yields of bioenergy crops., type: model (from/to model))
  • Precipitation - grid (Monthly total precipitation., type: model (from/to model))
  • Regression parameters (Regression parameters of suitability assessment., type: external parameter)
  • 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)
  • Water stress - grid (Water stress is a basin scale indicator of the mean annual water demand to availability ratio. This ratio gives an indication for the level of water stress experienced in the basin. Basins with a water demand to availability ratio above 0.2 are considered medium water stressed, basins with ratios above 0.4 are severely water stressed., type: model (end-indicator))

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