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Crop water productivity mapping using remote sensing and secondary data in the nile basin, midterm workshop
 

Crop water productivity mapping using remote sensing and secondary data in the nile basin, midterm workshop

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    Crop water productivity mapping using remote sensing and secondary data in the nile basin, midterm workshop Crop water productivity mapping using remote sensing and secondary data in the nile basin, midterm workshop Presentation Transcript

    • Crop Water Productivity Mapping Using Remote Sensing and Secondary Data in the Nile Basin Poolad Karimi Addis Ababa NILE BFP midterm workshop 07 April 2009
    • Introduction
      • Rapid increase in agricultural production will be required to keep pace with future food and fiber demands.
        • This can be achieved by bringing more area under agriculture or
        • by increasing the yields using similar or even reduced water resources (e.g., increasing productivity of water ) .
      • Considering that:
        • Land and water resources are already reached their exploitation limits or are over exploited in many river basins; and
        • There is increasing competition for water among sectors.
      • The option of increasing agricultural production using same or less water resources is the most appropriate one.
    • Water productivity mapping: METHODOLOGY (Molden 1997) Source: IWMI, 1997
      • Land use and land cover map : Global Cover Land Cover 2008 by European Space Agency: Its 22 land cover global classes are defined with the UN Land Cover Classification System (LCCS). The product pixel size is 300m. Croplands clases in the map are as fallows:
      • - Post-flooding or irrigated croplands (or aquatic)
      • - Rainfed croplands
      • - Mosaic cropland (50-70%) / vegetation (grassland/shrubland/forest) (20-50%)
      • - Mosaic vegetation (grassland/shrubland/forest) (50-70%) / cropland (20-50%)
      • Doesn't give us Crop type map
      • IFPRI 1 production maps
      IFPRI 1: International Food Policy Research Institute
      • Actual evapotranspiration (ETa):
      • Water watch ET map for 2007 (Wim/Yasir). The map pixel size is 1Km.
      • Secondary administrative agricultural statistics
      • - Ethiopia : Central Statistical Agency (CSA)
      • - Sudan: Sudan Central Bureau of Statistics
      • How can we get the same data for other countries particularly Egypt ?
    • Crop water productivity in Ethiopian part of the Nile Basin Source: Created by Karimi,P.
    • Rainfall and Water Consumption in 2007
      • Precipitation:
      • 1043 mm
      • Average ETa:
      • 730 mm
      • Overall Crop GVP:
      • 4.4×10 9 $/year
      Source: Created by IWMI using data from FEWS, 2009 Source: Created by IWMI using data from Waterwatch, 2009
    • Crops water consumption and economical land productivity
      • Eta Crops: 4500 m 3 /ha;
      • 1542 m 3 /ha to 7500 m 3 /ha
      • Eta per ha is lower in the eastern part
      • Crop GVP: 540 US$/ha
      • 286 US$/ha to 822 US$/ha
      • High performing areas in terms of Crop GVP/ha are:
      • - Shaka, Benchi Maji, Jimma and West Gojam
      Source: IWMI, 2009 Source: IWMI, 2009
    • Sub-Basin to Basin Scale Analysis: WP of vegetative and livestock
      • Crop WP: 0.16 $/m 3 ; 0.004 to 0.30 $/m 3 .
        • The higher values are mainly due to higher proportion of irrigated lands
      • Agricultural economic water productivity is higher in the eastern part
      • could it be due to high evaporation in cropped area and not transpiration in western part??
      Source: IWMI, 2009
    • Crop water productivity in Sudanese part of the Nile Basin Total cropped area: Secondary Stat: 14,860,440 GLC: 12,298,145 FAO: 12,849,520 Source: IWMI, 2009
    • Crop GVP VS Livestock GVP
      • Growth of livestock production value in last years
      • Importance of Livestock in Water productivity calculation
      Source: Graphs created by Karimi, P using data from FAO
    • Summary ,Conclusions and Questions
      • Secondary statistical data together with remote sensed data could be used to Map economic water productivity but it depends on how accurate are they.
      • Getting IFPRI Production maps seems to be very crucial to evaluate these result also to use to produce spatial distributed WP map for entire Nile
      • Use of Biomass to get physical WP and try to convert it to economical WP - it needs a crop type map and accuracy of results would be highly dependent on accuracy of the crop type map
      • How to join livestock WP and Fisheries WP with crop water productivity to create an overall water productivity map?
    • Thank You Related Project Report Forthcoming . For more information visit: www.iwmi.org www.waterandfood.org N.B. This is not a form of technical output. Data and figures shown are subject to change.