World wide Monitoring System
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1 Crop Monitoring and Early Warning for Food-Security, the MARS-FOOD Approach Felix Rembold MARS-FOOD Action / AGRIFISH Unit Institute for Protection and Security of the Citizen
2 MARS-FOOD Context and Objectives Canada 3% Japan 4% Food Aid by donor (2003) China 2% Others 9% Korea 5% USA 56% European Union 21% EU Food Aid in Africa (2003) Food Security, a major issue European Food Aid The EC needs information : To better calibrate European Food Aid POLICY DGS FAO WFP To contribute to Food Security JRC JRC MARS-FOOD Response : A Global Crop Monitoring System A Pool of Expertise in Food Security Support to UN and national Food Security agencies
3 MARS-FOOD Crop Monitoring System Data collection & retrieval Reporting Processing & Analysis Dissemination # Y Djibouti Mud C-NDVI Awdal Galbeed Ethiopia Galgadud Tog- class "isolated fields/ rainfed" Agro-pastoral sorghum Bakool Hiran Somalia Gedo 0.6 Middle 0.4 Shabelle 0.3 Bay #Mogadishu Y Lower Shabelle Middle Juba 80 rain Average mm Earth Observation Data Bakool Data Dissemination M A M J J A S O N D J F Time Lower Juba Crop GMS Meteorological Data Cumulated Precipitation Iran (south) mm 400 Bulletin Dissemination Sep1 Oct1 Nov1 Dec1 Jan1 Feb1 Mar1 Apr1 May1 Jun1 Jul1 Aug1 deka ds 2003/2004 Agronomic Database 2002/2003 WS Index Kenya Percentage of maize area in each class 100% 80% WEB Information Media Monitor 60% 40% 20% 0% Crop Assessment Process - DG AIDCO, ECHO, - EU Delegations - National EW Agencies - Int. Institutions (FAO, ) -
4 World wide Monitoring System -In 2005: 39 countries covered by 84 crop reports (10-daily to bi-monthly) Mediterranean Basin Russia & Central Asia Eastern Africa South America
5 MARS-FOOD Bulletin (East Africa 2005) regional reports AnMonthly elaborate crop specific water East Africa status 10/2005 balance model Real-time input Data NDVI from SPOT-4 Satellite Rainfall and PET from ECMWF model CPSZ Database Reference Data Soil information and Water Holding Capacity Historical Rainfall and PET Length of Growing Period for Determining Seasonal Plant water consumption Spatialization of grid data using AgrometShell Outputs directly usable by food security administrators Water Satisfaction Index for the Sorghum crop (October 2005) Difference with Normal WSI of Sorghum (Average of the last 6 years) Dekadal Rainfall and PET Images Specific crop mask from CPSZ database using Arc View GIS 3.2 Agrometeorological information was averaged for the 1,220 CPSZ units (van Velthuizen et al, 1995) Derived Database Spatial averaging of NDVI by CPSZ unit using Windisp4 Dekadal Rainfall and PET images Historical Planting Dekad Historical WSI and Yield estimates Specific crop mask and map expression using Arc View GIS 3.2 CPSZ NDVI profile analysis as Crop Yield Indicator Input data Crop planting analysis and crop cycle progress index Process and tools Running FAO Crop Specific Water Balance Model using Agromet Shell (Gommes, 1993) Crop Yield Function 1-Ya/Ymax= Ky *(1-ETa/ETmax) Ya=t/ha (Doorenbos and Kassam, 1979) Qualitative crop yield assessment using the Water Satisfaction Index (WSI) Quantitative Crop Yield assessment (t/ha) Intermediate and final outputs 2005 : Drop in Sorghum production as compared to normal conditions (potentially 11 Million people affected)
6 MARS-FOOD Special Bulletin on pasture (February 2006)
7 MARS-FOOD Bulletin (Somalia ) 10-daily country reports Somalia status 30/11/2005 Forecast for Sorghum Deyr 2005 : expected yield is below average and previous season. Pastoral vegetation in Southern Somalia affected by severe drought
8 Drought Monitoring in Northern Argentina, 2005 Rainfall, july/2005 Impact on vegetation in cropping areas, september/2005 (crop failure/human water supply problems in Chaco and Santiago del Estero)
9 MARSOP Site for information dissemination Main METEO and satellite base indicators On-the-fly subnational data analysis Main GWSI indicators available
10 MARS-FOOD in movement Pool of Expertise in Food Security 2006 and after - New expertise in vulnerability and need assessments (2006); - Improve quantitative yield forecasts; - Automation and convergence of bulletin preparation procedures; - Increase technical support to EC Delegations, UN agencies, National food sicurity institutions; - Contribute to the African Observatory for Sustainable Development.
11 Thank you
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