Presentation on theme: "SADC activities on the use of GIS and RS for Agricultural Meteorology"— Presentation transcript:
1 SADC activities on the use of GIS and RS for Agricultural Meteorology T. Tamuka MagadzireSADC Regional Remote Sensing Unit, USGS/FEWSNETWMO/FAO Training Workshop on GIS and Remote Sensing Application in Agricultural Meteorology for SADC Countries.November 14-18, 2005Gaborone, Botswana
2 Outline Background to SADC Region SDC RRSU Background Available EO-based dataModelling Applications of EO dataEnd-user information productsRRSU DatabasePartnerships - GMFS
3 The SADC Region - Background Southern African Development Community14 Member States.200+ million people.Varied climate regions.Mostly uni-modal rainfall systems (bi-modal in the north).Varied cropping systems.Maize (corn) dominant cropCassava and tubers important in the north.Rain fed agriculture – irrigation only significant in South Africa and Zimbabwe.Prone to floods and droughts.
4 Climatic Hazards in SADC The SADC Region - BackgroundClimatic Hazards in SADCFloods and droughts are the major climatic hazards in the SADC Region.Serious drought in :Flooding in Mozambique, Zimbabwe, Botswana and South Africa in 2000:Cyclones Eline and Gloria responsible.4 million people affected. Lessons learnt.SADC Disaster Management Strategy formulated.Further flooding in ensuing years (e.g. in 2003 from Cyclone Delfina (January) and Cyclone Japhet (March))Serious droughts between 2001 and 2005 in several SADC countries:
6 SADC RRSU: Organizational Context The SADC Secretariat is comprised of four directorates, including the Food, Agriculture and Natural Resources (FANR) DirectorateThe SADC Regional Remote Sensing Unit (RRSU) is a project within the FANR Directorate
7 Institutional Setting SADC RRSU Cooperating Partners:Technical support and training.Emergency food assessments.Supply of satellite data.Vulnerability assessment activities.Support to the Regional Disaster Management Strategy.
8 Main Objective of RRSUStrengthen national and regional capabilities in the area of Remote Sensing, Agrometeorology and GIS.Support early warning for food security and natural resources and disaster management.Principal contact institutions:National Meteorological Services (NMSs).National Early Warning Units (NEWUs).National Disaster Management Units.
9 SADC RRSU: Operational Activities Training of agro-meteorologists in the use of satellite imagery products and GIS for early warning for food security.Monitoring crops, vegetation and weather developments during the crop growing period using satellite images and GIS techniques.Developing and maintaining database of satellite images, maps and associated data.
10 RRSU: Agromet & GIS Training Creating trained experts in RS and GIS applications.National staff seconded to RRSUBackstopping missions organized for on-the-job training in Member States.Subject- or application- specific workshops conducted at national and regional levels.
11 SADC Region Early Warning Information flow Outgoing: satellite-based information and analysisNEWUNEWUNEWUNEWUNEWUNEWUNEWUNEWUNEWU
12 SADC Region Early Warning Information flow Incoming: ground-based information and analysisNEWUNEWUNEWUNEWUNEWUNEWUNEWUNEWUNEWU
13 Available EO-based Data Available satellite-based data used for Agromet activities are vegetation products and rainfall estimates.These products are analyzed and further processed into application specific products for flood and drought monitoring by USGS/FEWSNET and RRSU
14 Monitoring Rainfall Activity Rainfall Estimate (RFE) images.Combine satellite images with rain gauge observations.RRSU receives RFE images from USGS – EROS Data Center.
15 NOAA Rainfall Estimates Rainfall Estimates (RFE) are produced by NOAA for the FEWSNET activity, and distributed in southern Africa through RRSUUses a number of datasetsMeteosat data used to composite a CCD image at -38oC, a rainfall estimate is generated from the CCD using the GOES Precipitation Index (GPI). GPI = CCD x 3WMO GTS rainfall data from approx stations (not all stations used at any given time), and are taken as the true rainfall within 15-km radius of each stationTwo satellite microwave instruments, SSM/I (Special Sensor Microwave/Imager) and the AMSU (Advanced Microwave Sounding Unit), which acquire data every 6 hours and every 12 hours respectively.The four datasets are merged to produce an improved product
16 RFE – Related Activities SADC RRSU operates the WinTRES system and generates daily and dekadal Cold Cloud Duration (CCD) images from Meteosat-7 TIR imagesRRSU currently working on computer algorithms in collaboration with Botswana Met Services to enable the use of MSG Meteosat-8 images in CCD generationInterest has been expressed by SADC nationals in improving RFE using local rain gauge dataSome workshops have been held by NOAA on implementation of their RFE production technique locally in Africa – RRSU installed this technique locally for short timeLimited by operational availability of rain-gauge information
17 Monitoring Vegetation Condition Normalized Difference Vegetation Index (NDVI) images.Sources of NDVI are NOAA AVHRR (8km), SPOT VGT (1.1km) and MODIS (250m)MODIS: 250mAVHRR: 8 kmSPOT: 1 km
18 Seasonal Trends Time series curves for visualizing seasonal trends. Comparing against long-term (average) trends.Main crop-growing regions in SADC monitored.
19 Monitoring Crop Condition: WRSI The Water Requirements Satisfaction Index (WRSI) is a crop specific water balance approach that models the effect of seasonal rainfall availability on potential crop yields.Two approaches are used in the SADC region – using satellite-based, distributed approach, and a ground-based point-specific approachThe model is being used in several SADC countries to monitor crop water use with a view to yield forecasting and estimation. SADC RRSU is providing trainingOperational model run at USGS but modern modelling software now publicly available from FAO and USGS.
20 Crop Water Balance Modeling Water Requirements Satisfaction IndexCrop Water Balance ModelingWater Requirements Satisfaction Index (WRSI)WRSI=100*AET/WRRegression modelsYield Estimation
21 WRSI Water Balance - Products WRSI AnomalyStart of SeasonSoil Water Index
22 Can model for multiple regions or countries SWI, West AfricaWRSI Anom, East AfricaSOS, Southern AfricaCan model for multiple regions or countriesCan enter field information on planting, soils, maturityCan model using information formultiple planting datesmultiple varieties (maturity periods)multiple crop typesRange of outputs: SOS, WRSI, WRSI Anom, SWI etcWRSI, Zambia
23 End-user Information Products A number of bulletins are produced to meet information requirements, including:Regular agrometeorological updates at 10-daily and monthly intervalsAd-hoc “Significant Weather Developments” (SWD) bulletin which aims to “ provide timely highlights of developing weather patterns and their potential impacts to human lives and property”Other special bulletins to address current or issues e.g. forecast interpretation; drought alert
24 Agro-Meteorological Update RainfallAreasCropsModelsAgromet Up-datesSatellite information on rainfall and vegetation. Ground information on areas, crops and rainfall. Model outputs, e.g., WRSI to yield translation.
25 Agro-Meteorological Update RainfallAreasCropsModelsSatellite information on rainfall and vegetation. Ground information on areas, crops and rainfall. Model outputs, e.g., WRSI to yield translation.
26 Significant Weather Developments Forecast Cyclone TracksMajor River Basins
28 RRSU Database Developed and maintained on central computer at the RRSU Abridged onto CD for external use.Simple and open data formats make data portable.RRSU Standard Vector Data.Satellite data.Raster images with climatic parameters.Tabular data with agricultural statistics and population data.Free WinDisp 3.5 & 4 software for data viewing.Current CD-ROM version is 2.0.Details from
29 RRSU Data holdingscomprises both baseline datasets and earth observation datasets, compiled from a variety of sourcesuniform regional standard vector data set for SADC at a scale of 1:1 million was compiled as part of this datasetoriginated from the DCWupdated using inputs from the SADC countries
30 RRSU Data holdingsAdministrative (borders, subnational boundaries, cities)ElevationLand use and land coverHydrology (water bodies, rivers, lakes)Infrastructure (roads, railroads, bridges, airports, utility lines)SoilAgriculture (crop zone maps)Climate (rainfall, temperature etc)DemographySatellite images
31 RRSU Data holdings Administrative National borders of SADC countries Sub-national boundaries of SADC countriesNational borders of SADC countries (FAO/GIEWS version)Level 1 sub-national boundaries of SADC countries (FAO/GIEWS version)Major cities and towns of SADC countries (FAO/GIEWS version)Cities and towns of SADC countriesUrbanised areas of SADC countriesCultural landmarks of SADC countriesElevationDigital elevation modelElevation contours in SADC countriesSpot elevations in SADC countriesLand use and land coverLand cover areas of SADC countriesForest types in SADC countriesManaged areas (including national parks) in SADC countriesCentre points of managed areas in SADC countriesHydrologySmall water bodies of SADC countriesRivers of SADC countriesSurface water bodies of SADC countriesPerennial and non-perennial water layers in SADC countriesWetland types in SADC countriesLakes of SADC countriesSmall islands and lakes of SADC countriesSmall coastal islands of SADC countriesInfrastructureRoads in SADC countriesRailroads in SADC countriesRoad and Railroad Bridges in SADC countriesAirports in SADC countriesUtility lines in SADC countriesSoilSoil types in SADC countriesAgricultureCrop zone maps of SADC countries (FAO/GIEWS version)Crop harvest dates of SADC countries (FAO/GIEWS version)Crop planting dates of SADC countries (FAO/GIEWS version)Historical crop statistics for the SADC countriesCrop Water Satisfaction index (1996 – 2005)Start of rainfall season estimates ( )ClimateDekadal, long term average: rainfall, temperature, evapotranspirationMonthly, long term average: radiation, humidity, windSatellite Rainfall estimates from 1995 to 2005DemographyPopulation for SADC countries, by provinceSatellite imagesMODIS imagery ( )AVHRR NDVI vegetation images ( )Landsat imagery: regional coverage for 1970s, 1990s, 2000sASTER (partial SADC coverage) imagery for late 2001, early 2002, and 2003Meteosat thermal infrared and cold-cloud duration imagerySPOT-4 VGT NDVI vegetation images ( )
32 Partnerships - GMFSSADC RRSU has been collaborating with the GMFS consortium over the last couple of yearsGMFS is developing products for estimation of yield and area planted to crops, as well as other monitoring productsConcentrating on using a combination of SAR and optical EO data to id crop extent and phenological stagesGMFS has done some preliminary work for product development in Malawi, with potential for spreading to SADC regionProducts are currently being validated by GMFS
34 Re a lebohaGrazieZikomoObrigadoThank YouTinotendaGraciasSiyabongaAsante sanaMerci Beaucoup
35 Websites for cyclone monitoring Forecasted cyclone track:Latest cyclone track:Latest satellite imagery:Other useful websites for extreme-weather monitoring:Note: Although the SADC national meteorology websites have not been included here, they are very good for monitoring. Links to most of them can be found at:???
36 * Note that the merging process makes these datasets complementary NOAA RFE - LimitationsWeaknesses in datasetsMicrowave inputs have 6hr and 12hr repeat rate: estimates can either miss out some storms altogether, or overestimate rainfall when the satellite image is taken at the peak of a stormRainfall is estimated most accurately in the vicinity of GTS gaugesMeteosat-derived GPI estimates capture convectional rainfall very well. However, other rainfall types (e.g. orographic) are not estimated as accurately. Also cirrus clouds can cause over-estimation* Note that the merging process makes these datasets complementary