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Remote Sensing and Census Data Based Water Productivity Analysis for Limpopo Basin –  a preliminary report for discussion Xueliang Cai and Poolad Karimi Project Meeting, Pretoria 01 July 2009
Structure of the presentation ETa 1  – Actual Evapotranspiration Introd. Data ETa Introduction SGVP Data collection Simplified Surface Energy Balance model to calculate ETa 1   Standardized Gross Value of Production  Results The water productivity mapping results Discuss. Discussion and plan
What  is  WP? ,[object Object],Source: Molden,1997 Introd. Data ETa SGVP Results Discuss.
Why WP? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Introd. Data ETa SGVP Results Discuss.
Basin WP analysis – what to care? ,[object Object],[object Object],[object Object],[object Object],[object Object],Introd. Data ETa SGVP Results Discuss.
Water productivity mapping: METHODOLOGY Source: IWMI, 2009 Introd. Data ETa SGVP Results Discuss.
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data sources GLC: Global Land Cover IWMI GIAM: Global Irrigated Area Mapping Introd. Data ETa SGVP Results Discuss.
Land use and land cover map  Synthesized by combining the basin LULC map and South Africa Limpopo province map Source: Created by IWMI using data from the basin LULC map and South Africa Limpopo province map Introd. Data ETa SGVP Results Discuss.
Actual ET estimation - SSEB ET a   – the actual Evapotranspiration , mm. E T f  – the evaporative fraction , 0-1, unitless. ET 0  – Potential ET, mm. T x   –  the Land Surface Temperature (LST)  of pixel x from thermal data. T H /T C   – the LST of hottest/coldest  pixels . Simplified surface energy balance (SSEB) is a ET estimate model proposed by Senay (2007). It combines remotely sensed thermal imagery with ground measured climate data, providing quick ET estimate for large scale areas. Introd. Data ETa SGVP Results Discuss.
Actual ET estimation - SSEB Step 1 .  Potential ET calculation (2005 Apr 23 - 30 as example) ,[object Object],[object Object],Weather stations Source: IWMI Introd. Data ETa SGVP Results Discuss.
Actual ET estimation - SSEB Step 2.  Actual ET calculation by Simplified Surface Energy Balance (SSEB) approach Actual ET map  (2005 Apr 23 - 30) ET fraction map DEM corrected MODIS LST  potential ET map Source: IWMI Introd. Data ETa SGVP Results Discuss.
Standardized gross value of production  SGVP:  is an index which helps to compare the economical value of different crops regardless in which country or region they are. Maize  is  the  major crop in the basin and it is taken as base crop. Source: Molden, 2001 Introd. Data ETa SGVP Results Discuss.
Introd. Data ETa SGVP Results Discuss. ,[object Object],[object Object],Evapotranspiration Limpopo basin annual ETo map 2005  Limpopo basin annual ETa map 2005  Source: IWMI
Evapotranspiration Average ETa is  less than half  of ETo, indicating significant water stress Source: IWMI Introd. Data ETa SGVP Results Discuss. ETa: 779 mm ETo: 1676 mm Histogram ET (mm)
Evapotranspiration Source: IWMI CLASS_NAME Area LULC  Ratio ETa_ MEAN ETa_ STD ETa_ SUM Rainfall_ MEAN   [km 2 ] [%] [mm] [mm] [10 6  m 3 ] [mm] Waterbodies 124 0.0 861.8 220.3 106.9 550.6 Rock, mines, scars, river bed 299 0.1 737.7 163.9 220.8 506.7 Shrubland 255578 61.7 776.2 244.9 198387.9 580.2 Urban, builtup 2412 0.6 646.1 219.1 1558.3 627.2 Wetland 20 0.0 607.5 89.7 12.1 501.2 Grassland 5964 1.4 634.6 187.8 3784.8 527.5 Deciduous Broadleaf Forest 48999 11.8 791.5 197.3 38781.2 519.4 Evergeen Broadleaf Forest 1392 0.3 812.1 393.9 1130.8 677.4 Cropland/Grassland  Mosaic 69302 16.7 733.7 154.5 50844.2 619.8 Cropland/Woodland Mosaic 3583 0.9 927.5 347.9 3323.5 701.8 Dryland Cropland and pasture 9526 2.3 753.7 279.8 7179.5 597.2 Commercial irrigated, permanent 581 0.1 900.5 204.7 522.8 565.5 Commercial irrigated, temporary 1618 0.4 761.2 201.9 1231.5 541.9 Commercial dryland, permanent 417 0.1 986.4 231.3 411.8 613.6 Commercial dryland, temporary 6760 1.6 617.3 172.3 4173.0 554.1 Semicommercial dryland, temporary 7941 1.9 657.0 197.8 5217.6 550.7 Average     779.0 208.0   592.2 SUM 414517       316886.5  
SGVP SGVP calculate based on FAO data  While SGVP calculated using countries major crops production value at  Source: IWMI Country Total Cropped are a (ha) Total SGVP (Million US$) Average SGVP (US$/ha) Major cultivated crops Crop Yield (kg/ha) Percentage of cropped area Contribution to total SGVP South Africa 6,043,944 8,216.4 1,360 Maize 3,635 53% 17% Wheat 2,366 13% 5% Sunflower  1,348 8% 2% Mozambique 4,525,760 1,068.3 286 Maize 1,141 27% 16% Cassava 5,882 24% 55% Sorghum 629 11% 3% Zimbabwe 2,975,330 1,724.7 580 Maize 529 58% 7% cotton 668 10% 8% Groundnuts 288 7% 1% Botswana 142,525 Introd. Data ETa SGVP Results Discuss.
SGVP The SGVP figures estimated through country statistic  for the part fall in the basin boundary: - South Africa;  450   US$/ha  ; from  442  to  453   US$/ha  - Mozambique;  80   US$/ha  ; from  47  to  126   US$/ha Which much are  lower than  the one calculated by FAO data.  Within the Mozambique districts  Beline, Chibuto  and  Xai xai  Districts in south  east part of the basin have higher SGVP  Whereas,  Chicualacuala  has the lowest  Source: IWMI Introd. Data ETa SGVP Results Discuss.
WP Source: IWMI Introd. Data ETa SGVP Results Discuss.
Causes for variations and scope for improvement Source: IWMI Introd. Data ETa SGVP Results Discuss.
Causes for variations and scope for improvement Source: IWMI
Basin water productivity analysis - the road ahead ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Introd. Data ETa SGVP Results Discuss.
Thank You Project Report, Forthcoming. For more information visit: www.iwmi.org N.B. This is not a form of technical output.  Data and figures shown are subject to change .

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Remote sensing and census data water productivity analysis for limpopo basin

  • 1. Remote Sensing and Census Data Based Water Productivity Analysis for Limpopo Basin – a preliminary report for discussion Xueliang Cai and Poolad Karimi Project Meeting, Pretoria 01 July 2009
  • 2. Structure of the presentation ETa 1 – Actual Evapotranspiration Introd. Data ETa Introduction SGVP Data collection Simplified Surface Energy Balance model to calculate ETa 1 Standardized Gross Value of Production Results The water productivity mapping results Discuss. Discussion and plan
  • 3.
  • 4.
  • 5.
  • 6. Water productivity mapping: METHODOLOGY Source: IWMI, 2009 Introd. Data ETa SGVP Results Discuss.
  • 7.
  • 8. Land use and land cover map Synthesized by combining the basin LULC map and South Africa Limpopo province map Source: Created by IWMI using data from the basin LULC map and South Africa Limpopo province map Introd. Data ETa SGVP Results Discuss.
  • 9. Actual ET estimation - SSEB ET a – the actual Evapotranspiration , mm. E T f – the evaporative fraction , 0-1, unitless. ET 0 – Potential ET, mm. T x – the Land Surface Temperature (LST) of pixel x from thermal data. T H /T C – the LST of hottest/coldest pixels . Simplified surface energy balance (SSEB) is a ET estimate model proposed by Senay (2007). It combines remotely sensed thermal imagery with ground measured climate data, providing quick ET estimate for large scale areas. Introd. Data ETa SGVP Results Discuss.
  • 10.
  • 11. Actual ET estimation - SSEB Step 2. Actual ET calculation by Simplified Surface Energy Balance (SSEB) approach Actual ET map (2005 Apr 23 - 30) ET fraction map DEM corrected MODIS LST potential ET map Source: IWMI Introd. Data ETa SGVP Results Discuss.
  • 12. Standardized gross value of production SGVP: is an index which helps to compare the economical value of different crops regardless in which country or region they are. Maize is the major crop in the basin and it is taken as base crop. Source: Molden, 2001 Introd. Data ETa SGVP Results Discuss.
  • 13.
  • 14. Evapotranspiration Average ETa is less than half of ETo, indicating significant water stress Source: IWMI Introd. Data ETa SGVP Results Discuss. ETa: 779 mm ETo: 1676 mm Histogram ET (mm)
  • 15. Evapotranspiration Source: IWMI CLASS_NAME Area LULC Ratio ETa_ MEAN ETa_ STD ETa_ SUM Rainfall_ MEAN   [km 2 ] [%] [mm] [mm] [10 6 m 3 ] [mm] Waterbodies 124 0.0 861.8 220.3 106.9 550.6 Rock, mines, scars, river bed 299 0.1 737.7 163.9 220.8 506.7 Shrubland 255578 61.7 776.2 244.9 198387.9 580.2 Urban, builtup 2412 0.6 646.1 219.1 1558.3 627.2 Wetland 20 0.0 607.5 89.7 12.1 501.2 Grassland 5964 1.4 634.6 187.8 3784.8 527.5 Deciduous Broadleaf Forest 48999 11.8 791.5 197.3 38781.2 519.4 Evergeen Broadleaf Forest 1392 0.3 812.1 393.9 1130.8 677.4 Cropland/Grassland Mosaic 69302 16.7 733.7 154.5 50844.2 619.8 Cropland/Woodland Mosaic 3583 0.9 927.5 347.9 3323.5 701.8 Dryland Cropland and pasture 9526 2.3 753.7 279.8 7179.5 597.2 Commercial irrigated, permanent 581 0.1 900.5 204.7 522.8 565.5 Commercial irrigated, temporary 1618 0.4 761.2 201.9 1231.5 541.9 Commercial dryland, permanent 417 0.1 986.4 231.3 411.8 613.6 Commercial dryland, temporary 6760 1.6 617.3 172.3 4173.0 554.1 Semicommercial dryland, temporary 7941 1.9 657.0 197.8 5217.6 550.7 Average     779.0 208.0   592.2 SUM 414517       316886.5  
  • 16. SGVP SGVP calculate based on FAO data While SGVP calculated using countries major crops production value at Source: IWMI Country Total Cropped are a (ha) Total SGVP (Million US$) Average SGVP (US$/ha) Major cultivated crops Crop Yield (kg/ha) Percentage of cropped area Contribution to total SGVP South Africa 6,043,944 8,216.4 1,360 Maize 3,635 53% 17% Wheat 2,366 13% 5% Sunflower 1,348 8% 2% Mozambique 4,525,760 1,068.3 286 Maize 1,141 27% 16% Cassava 5,882 24% 55% Sorghum 629 11% 3% Zimbabwe 2,975,330 1,724.7 580 Maize 529 58% 7% cotton 668 10% 8% Groundnuts 288 7% 1% Botswana 142,525 Introd. Data ETa SGVP Results Discuss.
  • 17. SGVP The SGVP figures estimated through country statistic for the part fall in the basin boundary: - South Africa; 450 US$/ha ; from 442 to 453 US$/ha - Mozambique; 80 US$/ha ; from 47 to 126 US$/ha Which much are lower than the one calculated by FAO data. Within the Mozambique districts Beline, Chibuto and Xai xai Districts in south east part of the basin have higher SGVP Whereas, Chicualacuala has the lowest Source: IWMI Introd. Data ETa SGVP Results Discuss.
  • 18. WP Source: IWMI Introd. Data ETa SGVP Results Discuss.
  • 19. Causes for variations and scope for improvement Source: IWMI Introd. Data ETa SGVP Results Discuss.
  • 20. Causes for variations and scope for improvement Source: IWMI
  • 21.
  • 22. Thank You Project Report, Forthcoming. For more information visit: www.iwmi.org N.B. This is not a form of technical output. Data and figures shown are subject to change .