1. SADC Agricultural Information Management System: Crop and Rangeland Monitoring Activities for Early Warning for Food Security Blessing Siwela, Agricultural Information Officer, SADC FANR

2. Outline Background to SADC Region About SADC FANR, Agricultural Information Management System (AIMS) Crop and Rangeland Monitoring approach Data / information gathering mechanisms Use of Earth Observation data for season crop and rangeland monitoring Main indicators of crop condition used Information Dissemination approaches Challenges Upcoming developments

3.  15 Member States  220+ million people.  Varied climate regions.  Mostly uni-modal rainfall systems (bi-modal in the north).  Varied cropping systems.  Cereal cropping dominant (Maize, sorghum, millet, wheat)  Cassava and tubers important in the north.  Rain fed agriculture – irrigation only significant in South Africa and Zimbabwe.  Main Livestock types include cattle, goats, sheep  Prone to floods and droughts.  Other main challenges include bush fires, deforestation. SADC Region - Background Southern African Development Community

4. Agricultural Information Management System (AIMS) The Agricultural Information Management System (AIMS) programme is meant to provide planners and policy makers easy access to information necessary for revitalizing agricultural and natural resources growth, enhancing food security and promoting rural development. Activities include: – development of networks for timely collection of information for early warning, – vulnerability assessments, – food security assessments, – establishment of a Food, Agriculture and Natural Resources’ integrated database on food security and natural resources

5. AIMS: Operational Activities Supporting agro-meteorologists in the use of satellite imagery products and GIS for crop and rangeland for food security. Monitoring crops, vegetation and weather developments during the crop growing period using satellite images and GIS techniques. Collection of information on agriculture (crop and livestock performance) from national contacts Preparing and disseminating reports on the status of the main crop growing season, and the food security situation in SADC countries

6. AIMS: Operational Activities Countries Website Bulletins Country Windows Image Review / analysis E-mail USGS/ FEWSNET VITO AMESD SADC Archive E-mail / internet Acquisition and distribution of remote sensing datasets used for crop and rangeland monitoring

7. Crop and Rangeland Monitoring approach  Identify the key cropland and rangeland areas for monitoring  Collection of information from National Early Warning Systems  Climate / weather outlooks, Rainfall performance  Crop stages, crop and pasture condition  Hydrological information  Complement the information with remote sensing data  Use convergence of evidence to analyse and arrive at conclusions on the state of crops and rangeland  Identify “hot spots” for close monitoring  Prepare regular reports and distribute widely

8. Crop and Rangeland Monitoring approach key cropland and rangeland areas for monitoring identified through analysis of – historical yield and production information – livelihood analysis profiles FEWSNET FAO

9. Crop and Rangeland Monitoring approach Collection of information from National Early Warning Systems – Climate / weather outlooks, Rainfall performance – Farming inputs (machinery, fertilisers, seeds, etc) – Crop stages, crop and pasture condition – Livestock numbers and health – Hydrological information – Crop production estimates

10. NEWU Crop and Rangeland Monitoring approach Collection of information from National Early Warning Systems - How? – Bulletins are received from early warning systems via e- mail [10-day agrometeorological updates, monthly food security reports] – Questionnaires (hardcopy and electronic) send out to contact points – Information exchange by e- mail, telephone – Online forms for data collection are being introduced

11. Available Remote Sensing Data Available satellite-based data used for regular monitoring: –vegetation products (NDVI from SPOT VEGETATION, NOAA AVHRR, MSG) –rainfall monitoring (CPC RFE 2.0, TAMSAT RFE) These products are analyzed and further processed into application specific products for flood and drought monitoring Other datasets MODIS NDVI Vgt4Africa datasets (NDVI, DMP, NDWI, SWB, etc) LANDSAT ASTER

12. RFE is used to drive a number of applications used for agricultural season monitoring These include –Rainfall performance –Water Requirements Satisfaction Index (WRSI) –Onset of Rains –Soil Moisture Index –Quelea birds breeding forecasts Applications of CPC RFE data

13. Monitoring Rainfall Activity CPC Rainfall Estimate (RFE 2.0) data, which combines satellite images with rain gauge observations. RFE images from USGS / FEWSNET January 2008 rainfall estimates Mozambique, 2008 Zambia, 2008 Jan 1-10Jan 11-20Jan 21-31

14. Monitoring Rainfall Activity Time-series graphs Comparison with reference data (e.g. Averages) >>Image differencing >>Percentage maps Time series rainfall analysis Percentage cumulative rainfall received

15. Crop Condition Monitoring 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. WRSI indicates the extent (in percent) to which the water requirements of the crop has been satisfied in a cumulative way at any stage of the crop growing season. Two approaches are used in the SADC region – using satellite-based, distributed approach, and a ground-based point-specific approach The 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 training Operational model run at USGS but modern modelling software now publicly available from FAO (AgrometShell) and USGS (GeoSpatial WRSI).

16. Crop Water Balance Modeling Water Requirements Satisfaction Index (WRSI) WRSI=100*AET/WR Regression models Yield Estimation Water Requirements Satisfaction Index

17. Malawi WRSI yield modelling Water Requirements Satisfaction Index WRSI yield models are used operationally to provide early estimates of yield and production Higher correlations with yield in the southern parts of the country Lower correlations in the northern districts could be related to poor distribution of rainfall stations Main maize production areas [FEWSNET] WRSI / Yield R-Sq values

18. Swaziland WRSI yield modelling Water Requirements Satisfaction Index Swaziland yield models and their reliability Correlations with WRSI high in the main maize growing areas Poor correlations in Lowveld Main maize production areas [FEWSNET] WRSI / Yield R-Sq values

19. Monitoring of Pests : Quelea birds breeding forecasts Forecasting suitable breeding conditions for the red-billed quelea birds Based on daily rainfall (currently NOAA CPC estimates) and ancillary information on quelea birds Updated weekly Threats to small grain crops Developed by Natural Resources Institute of the University of Greenwich, www.nri.org http://www.sadc.int/fanr/aims/rrsu/quel/index.htm

20. Available NDVI datasets TypeResolutionFrequencySource NOAA AVHRR1.1km, 8km10 daysUSGS/FEWSNET SPOT VGT1.1km10 daysVITO MODIS250m, 500m16 daysUSGS METEOSAT-83kmBMS Receiver Vegetation Monitoring

21. Available NDVI datasets GAC 8km Source: USGS / FEWSNET 1982-current 21-31 January 2006 S-10 NDVI (MVC) from FAO ARTEMIS (via FTP) SADC-wide coverage EumetCast distribution via MSG receivers, http://www.vgt4africa.org Vegetation Monitoring

22. NDVI time-series analysis Time series analysis done for visualizing seasonal trends in the major agricultural areas Comparison with average and other seasons Vegetation Monitoring

23. NDVI trend series smoothing (Reed et al, 1999) February 11-20 2000 February 21-29 2000 March 1-10 2000 Weighted least squares approach to NDVI smoothing 5-dekad overlapping moving windows used Vegetation Monitoring

24. 2003 drought in parts of southern Africa VGT S-10 NDVI used in SADC report to show extent of drought SPOTVGTSPOTVGT Vegetation Monitoring

25. NDVI Based Indicators Vegetation Productivity Indicator (VPI) references current the NDVI value to its historical probability Developed at Cranfield University 20%40%60%80% Vegetation Monitoring

26. Information Products A number of bulletins are produced to meet information requirements, including: –Regular agro-meteorological updates at 10-day and monthly intervals –Ad-hoc “Significant Weather Developments” (SWD) bulletins which aim 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. Rainfall forecast interpretation; flood / drought alert E-mail distribution Websites: www.sadc.int/fanr/aims www.sadc.int/geonetwork/

27. Information Products AIMS online data visualisation tools – Crop production [national and provincial]

28. Information Products AIMS online data visualisation tools – Livestock health and numbers

29. Information Products AIMS online data visualisation tools – Populations vulnerable to food security

30. Information Products – Country Profiles AIMS online data visualisation tools – Country profiles

31. Information Products – Country Profiles AIMS online data visualisation tools – Country profiles

32. Agromet Up-dates Agric Areas Crops Rainfall Models Agric Activities Crops

33. Dry January conditions suggest a pre-mature cessation of short rains (Vuli) in the bi-modal rainfall areas of Tanzania. 2008-2009 Agriculture Season Jan 1 – Feb 10, 2009 Rainfall, Percentage of average 2009 rainfall has been below average in eastern Zimbabwe, and central and southern Mozambique, dry spells in these areas have resulted in moisture stress. Good crop conditions reported in South African high maize production areas. Consistent high rainfall totals in southern Angola and northern Namibia resulted in abnormally high river levels in the Cuvelai and Zambezi basin, causing extensive flooding. The flooding led to loss of lives, displacements of people and cattle, and also destroyed crops.

34. Significant Weather Developments Forecast Cyclone Tracks Major River Basins

35. Examples from SWD bulletins

36. Online Data Management Tools SADC GeoNetwork, www.sadc.int/geonetwork/www.sadc.int/geonetwork/ A web based open-source metadata catalogue application ISO19115/19139 Geographic Metadata standards GeoNetwork integrates – Search functions – Administrative functions – Data sharing - distribution and publication Developed by UN's FAO, WFP and UNEP to promote data sharing

37. Current main challenges Lack of resources for monitoring of agriculture by extension officers Ground rainfall observation networks and Data management – Awareness among decision makers on importance of these networks – Training of meteorological officers – Maintenance Reliability of rainfall estimates Identification of cropped areas Crop area estimation for food security analysis Availability software for analysis of early warning remote sensing and GIS datasets

38. Identified Areas of Need / Concern Agricultural Production Information  Rainfall amount and patterns  Crop Area Measurement  Yield Estimate  Crop Cycles Disaster Monitoring  Drought / Flood  Bush Fires  Cyclones  Pest and Diseases Natural Resources Management  Water bodies monitoring  Soil types and Fertility  Wetland status Land Management Information  Deforestation / afforestation  Alien Species Invasion  Grazing Capacity  Seasonal biomass monitoring  Classification of potential land uses  Demarcation of crop and range land

39. Upcoming Initiatives Collaboration with African Monitoring of the Environment for Sustainable Development (AMESD) on preparation of agro-meteorological reports – Theme: Agricultural and Environment Resource Management – Access to EO datasets – Information management aimed at improving decision making

40. Contacts For more information on the AIMS programme, contact – Blessing Siwela, bsiwela@sadc.intbsiwela@sadc.int – Bentry Chaura, bchaura@sadc.intbchaura@sadc.int Website: www.sadc.int/fanr/aims Thank You