This vector layer (polygon) – reference scale 1/200 000 – is an aggregated sub-basin delineation of the CORB-Contributing area,incorporating basins of the main tributaries only. It was created by aggregation of the sub basin units from the Sub Basins Level III. This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

Bias Correction of ERA-interim meteorological forcing dataset for Africa, based on Piani et al. (2010) for the period 1979 - 2011. Variables description Tair: air temperature (K) Tmin: minimum air temperature (K) Tmax: maximum air temperature (K) PSurf: surface pressure (Pa) Qmean: specific humidity (kg/kg) Wind: wind speed (m/s) Precip: precipitation (mm) LWdown: Downwards long-wave radiation flux (W/m-2) SWdown: Downwards short-wave radiation flux (W/m-2). This data set has been produced in the framework of the "Climate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)" project, Work Package 1 (WP1). WP1 (Past climate variability) aimed to provide consolidated data to other WPs in ClimAfrica, and to analyze the interactions between climate variability, water availability and ecosystem productivity of Sub-Saharan Africa. Various data streams that diagnose the variability of the climate, in particular the water cycle, and the productivity of ecosystems in the past decades, have been collected, analyzed and synthesized. The data streams range from ground-based observations and satellite remote sensing to model simulations. More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.

Vegetation classes according to White's (1983) classification within the Okavango Basin. Source: Vegetation Map of Africa, White 1983, UNESCO/AETFAT/UNSO. This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

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.

Delineation of aquifer systems in Angola, that share geographical overlapping with the Okavango Basin. Source: Generated for the EPSMO project based on hydrogeological map of Angola provided by Direccao de Geologia e Minas at 1/1000000. This dataset is part of the GIS Database for the Environment Protection and Sustainable Management of the Okavango River Basin project (EPSMO). Detailed information on the database can be found in the “GIS Database for the EPSMO Project” document produced by Luis Veríssimo (FAO consultant) in July 2009, and here available for download.

On the basis of soil parameters provided by the Harmonized World Soil Database (HWSD) seven key soil qualities important for crop production have been derived, namely: nutrient availability, nutrient retention capacity, rooting conditions, oxygen availability to roots, excess salts, toxicities, and workability. Soil qualities are related to the agricultural use of the soil and more specifically to specific crop requirements and tolerances. For the illustration of soil qualities, maize was selected as reference crop because of its global importance and wide geographical distribution. Toxicities (SQ.6) Low pH leads to acidity related toxicities, e.g., aluminum, iron, manganese toxicities, and to various deficiencies, e.g., of phosphorus and molybdenum. Calcareous soils exhibit generally micronutrient deficiencies, for instance of iron, manganese, and zinc and in some cases toxicity of molybdenum. Gypsum strongly limits available soil moisture. Tolerance of crops to calcium carbonate and gypsum varies widely (FAO, 1990; Sys, 1993). Low pH and high calcium carbonate and gypsum are mutually exclusive. Acidity related toxicities such as aluminum toxicities and micro-nutrient deficiencies are accounted for respectively in SQ1, nutrient availability, and in SQ2, nutrient retention capacity. This soil quality SQ6 is therefore only including calcium carbonate and gypsum related toxicities. The most limiting of the combination of excess calcium carbonate and gypsum in the soil, and occurrence of petrocalcic and petrogypsic soil phases is selected for the quantification of SQ6. Note that the classes used in the Soil Quality evaluation are: 1: No or slight limitations 2: Moderate limitations 3: Sever limitations 4: Very severe limitations 5: Mainly non-soil 6: Permafrost area 7: Water bodies Remember that classes are qualitative not quantitative. Only classes 1 to 4 are corresponding to an assessment of soil limitations for plant growth. Class 1 is generally rated between 80 and 100% of the growth potential, class 2 between 60 and 80%, class 3 between 40 and 60%, and class 4 less than 40%.

Relative humidity at 15h (local time) at a height of 2 metres above the surface. This variable describes the amount of water vapour present in air expressed as a percentage of the amount needed for saturation at the same temperature. Unit: %. The Relative humidity variable is part of the Agrometeorological indicators dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) through the Copernicus Climate Change Service (C3S). The Agrometeorological indicators dataset provides daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies. This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. References: https://doi.org/10.24381/cds.6c68c9bb The Copernicus Climate Change Service (C3S) aims to combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. ECMWF operates the Copernicus Climate Change Service on behalf of the European Union and will bring together expertise from across Europe to deliver the service.

Relative humidity at 18h (local time) at a height of 2 metres above the surface. This variable describes the amount of water vapour present in air expressed as a percentage of the amount needed for saturation at the same temperature. Unit: %. The Relative humidity variable is part of the Agrometeorological indicators dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) through the Copernicus Climate Change Service (C3S). The Agrometeorological indicators dataset provides daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies. This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. References: https://doi.org/10.24381/cds.6c68c9bb The Copernicus Climate Change Service (C3S) aims to combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. ECMWF operates the Copernicus Climate Change Service on behalf of the European Union and will bring together expertise from across Europe to deliver the service.

Mean wind speed at a height of 10 metres above the surface over the period 00h-24h local time. Unit: m s-1. The Wind Speed variable is part of the Agrometeorological indicators dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) through the Copernicus Climate Change Service (C3S). The Agrometeorological indicators dataset provides daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies. This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. References: https://doi.org/10.24381/cds.6c68c9bb The Copernicus Climate Change Service (C3S) aims to combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. ECMWF operates the Copernicus Climate Change Service on behalf of the European Union and will bring together expertise from across Europe to deliver the service.

Geo-referenced point database on dams in Africa.