From 1 - 4 / 4
  • Categories  

    This map represents the spatial distribution of land under irrigation which is affected by some degree of salinization. It was produced by combining FAO AQUASTAT country statistics regarding irrigated areas affected by salinization with spatial information on irrigated areas where precipitation is not sufficient to leach away salt residues that are built up in the soil due to irrigation. It was assumed that the risk of salinization of irrigated areas can occur only in areas with an Aridity Index lower than 0.65 (where the Aridity Index is defined as Yearly Precipitation divided by Yearly Reference Evapotranspiration).

  • Categories  

    The map summarizes the status of the land use and land cover at global scale. It was compiled according to the current GAEZ (Global Agro-Ecological Zones) -2009 approach, developed by FAO in collaboration with IIASA (International Institute for Applied Systems Analysis).The current Global AEZ (GAEZ-2009) offers a standardized framework for the characterization of climate, soil and terrain conditions relevant to agricultural production, which can be applied at global to sub-national levels. The map is based on six geographic datasets: - GLC2000 land cover database at 30 arc-sec (http://www-gvm.jrc.it/glc2000), using regional and global legends (JRC, 2006); - an IFPRI global land cover categorization providing 17 land cover classes at 30 arc-sec. (IFPRI, 2002), based on a reinterpretation of the Global Land Cover Characteristics Database (GLCC ver. 2.0), EROS Data Centre (EDC, 2000); - FAO’s Global Forest Resources Assessment 2000 and 2005 (FAO, 2001; FAO, 2006) at 30 arc-sec. resolution; - digital Global Map of Irrigated Areas (GMIA) version 4.0 of (FAO/University of Frankfurt) at 5’ by 5’ latitude/longitude resolution, providing by grid-cell the percentage land area equipped with irrigation infrastructure (Siebert et al., 2007); - a spatial population density inventory (30-arc seconds) for year 2000 developed by FAO-SDRN, based on spatial data of LANDSCAN 2003, with calibration to UN 2000 population figures. An iterative calculation procedure has been implemented to estimate land cover class weights, consistent with aggregate FAO land statistics and spatial land cover patterns obtained from remotely sensed data, allowing the quantification of major land use/land cover shares in individual 5’ by 5’ latitude/longitude grid cells.

  • Categories  

    The map shows the total annual water withdrawal. Water withdrawals are downscaled to to a five arc-minute grid. Water is considered scarce when the withdrawals exceed 40% of the renewable resource. According to statistics compiled by FAO (FAOSTAT), several countries in North Africa, the Middle East and Central Asia withdraw more water than their total renewable resources. Domestic water withdrawals are downscaled by applying the per capita domestic water use to population of each pixel. Industrial water withdrawals were downscaled by using the industrial water use per unit GDP and applying downscaled information on GDP. Water consumption is assumed to be 30% of domestic use and 10% of industrial use. Finally, agricultural water consumption is assumed to be the crop water deficit in irrigated areas generated in the AEZ analysis and water used for livestock consumption, applied to a global spatial data set of livestock distribution prepared by FAO. Source of the map: GAEZ 2009 and AQUASTAT; downscaling simulations by authors.

  • Categories  

    The map shows the ratio of total withdrawals to the available renewable water resource. Renewable water resources are downscaled to a five arc-minute grid. Water is considered scarce when the withdrawals exceed 40% of the renewable resource. According to statistics compiled by FAO (FAOSTAT),several countries in North Africa, the Middle East and Central Asia withdraw more water than their total renewable resources. Domestic water withdrawals are downscaled by applying the per capita domestic water use to population of each pixel. Industrial water withdrawals were downscaled by using the industrial water use per unit GDP and applying downscaled information on GDP. Water consumption is assumed to be 30% of domestic use and 10% of industrial use. Finally, agricultural water consumption is assumed to be the crop water deficit in irrigated areas generated in the AEZ analysis and water used for livestock consumption, applied to a global spatial data set of livestock distribution prepared by FAO.Source of the map: GAEZ 2009 and AQUASTAT; downscaling simulations by authors.