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Remote sensing and census data water productivity analysis for limpopo basin
 

Remote sensing and census data water productivity analysis for limpopo basin

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Remote sensing and census data water productivity analysis for limpopo basin. Xueliang Cai and Poolad Karimi. Project Meeting, Pretoria, 01 July 2009

Remote sensing and census data water productivity analysis for limpopo basin. Xueliang Cai and Poolad Karimi. Project Meeting, Pretoria, 01 July 2009

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    Remote sensing and census data water productivity analysis for limpopo basin Remote sensing and census data water productivity analysis for limpopo basin Presentation Transcript

    • 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?
      • Water productivity (WP) is “the physical mass or the economic value of production measured against gross inflow, net inflow, depleted water, process depleted water, or available water” (Molden, 1997, SWIM 1). WP measures how the systems convert water into goods and services. The generic equation is:
      Source: Molden,1997 Introd. Data ETa SGVP Results Discuss.
    • Why WP?
      • 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 land & water resources (e.g., increasing productivity of water ) .
      • Considering that:
        • Land and water resources have 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.
      Introd. Data ETa SGVP Results Discuss.
    • Basin WP analysis – what to care?
      • Magnitude – what’s the current status?
      • Causes – why is WP vary (both high and low)?
      • Irrigated vs. Rainfed – what are the options for sustainable development under water scarcity and food deficit condition ?
      • Crop vs. livestock and fisheries – how livestock and fisheries are contributing to water use outputs?
      • Scope for improvement – how much potential for where?
      Introd. Data ETa SGVP Results Discuss.
    • Water productivity mapping: METHODOLOGY Source: IWMI, 2009 Introd. Data ETa SGVP Results Discuss.
      • Production data:
      • - Countries statistic (Mozambique and South Africa)
      • - FAO database in 2005
      • Weather data daily temperature, humidity, sea level pressure, precipitation, wind speed collected for 18 stations
      • RS images and secondary GIS data
      • - MODIS 8-day land surface temperature (LST) products
      • - Land use/land cover (LULC); Basin LULC MAP/ GLC 2008/ IWMI GIAM
      • - Admin and basin boundaries, road network, ecological zones and DEM
      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)
      • Steps:
      • Hargreaves equation for reference ET.
      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.
      • Average ETo is 1676 mm - standard deviation of 148 mm
      • Average ETa is 779 mm - deviation of 208 mm.
      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
      • Issues need to be resolved:
      • Better basin land use and land cover map and assessment of the influences on final water productivity maps;
      • Validation of ET (with local expert knowledge);
      • Crop production data for a better land productivity map;
      • Livestock and fishery to be included in WP (data?);
      • Linkages with other work packages of Limpopo BFP ( especially water availability and interventions);
      • Field level water productivity assessment for validation and causes studies (scaling down/up).
      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 .