1. Agrometshell Workshop 15-17 September Rome

2. Peter Hoefsloot? Dutch National Married, 2 children, 7 sheep Msc. In Agronomy/Meteorology/Comp. Science in Wageningen, The Netherlands Do management of geo-info projects for Dutch consultancy firm (Haskoning) Have my own (little) company working for FAO and Dutch ministries writing software 1989 – 1991 : Agrhymet, Niger 1991 – 1994 : RRSU, Harare, Zimbabwe Many missions (most SADC and CILSS countries, Djibouti)

3. Parts of this demo A bit of history Objectives of AMS AMS seen from different perspectives General structure and functions Demonstration

4. A bit of history Drought sub-Sahara Africa (mid-seventies) : desertification 1974 - CILSS founded Agrhymet in Niamey (West Africa) 1986 - Intergovernmental Authority on Development (IGAD) formed Intergovernmental Authority on Drought and Development (IGADD) for East Africa in Djibouti Mid-eighties SADC – (Southern Africa) founded the Regional Early Warning Unit in Harare Now - New frontiers : Afghanistan, IRAQ, Bangladesh

5. Assisting “early warning” FAO (United Nations) GIEWS (Global Information and Early Warning System) and support for national and regional EW units ARTEMIS ( Africa Real Time Environmental Monitoring Information System ) USAID (United States) FEWS - Famine Early Warning System European Union Many institutes University of Venice, Italy University of Reading, UK (TAMSAT) ITC, The Netherlands USGS, United States (…)

6. What do you need for EW? Data and information Methods and models Software Facilities (computers, communication) Skilled staff

7. Data for early warning Stocks on staple foods Pricing of foods on markets Crop Yields Weather data (e.g. rainfall) through GTS (worldwide) and Met Services (national) Satellite data (mainly METEOSAT and NOAA) “Static” support data : maps, census data, agro-ecological zones, soil maps

8. Where do we get data from? Ministries and other government institutions Met Services Many internet sources ARTEMIS and AGROMET data information http://metart.fao.org/ Africa Data Dissemination Service http://edcw2ks21.cr.usgs.gov/adds/

9. Methods and models NDVI (Vegetation Greenness Monitoring); 1x1 km and 7x7 km Cold Cloud Duration (CCD) Rainfall estimates (RFE) Water Balance Models Statistics Interpolation

10. Software IDA- Windisp Agman – Priceman – Spaceman (USGS) FAOINDEX, FAOMET and others ADDAPIX  spatial and temporal analysis of satellite imagery MADAM  generation of multi-image statistics IGT  GIS and interpolation tools for IDA FAOCLIM  software and large agro-climatic database

11. Why write EW software? License free Moderate computing requirements Ease of use (WB in Excel is possible..) Possibility to create new analysis methods (SEDI, ADDAPIX) GIS systems require a lot of training, use large and complex data models, are not license free, use heavy computers

12. AgrometShell

13. AMS History 1989 : Niamey Niger : SUIVI 1992 : Harare Zimbabwe : SEDI and IGT 1995 – 2000 : SEDI updates From 2001 : AMS Promotors and sponsors : FAO Rome, Aghrymet, REWU Harare, IGADD

14. AgrometShell objectives Facilitate monitoring of growing season For national and regional EW units and international bodies like FAO Available license free Easy to use and well-documented Bridging the gap between agromet, remote sensing and socio-economic datasets Flexible toolbox to which others can contribute with code (e.g. Univ. of Louvain; interpol.) Exchange with other relevant software Windows rewrite of DOS software AMS will not provide functions other packages offer

15. AgrometShell in a nutshell FAO Crop Water Balance model Database for Agromet point data (SUIVI) Interpolation (SEDI, Inverse distance, Co- Kriging etc…) Statistics useful for Agromet Provide conversion functions between data files Viewer (every function ends with viewing results) Automation Some functions are in because unavailable in other EW software

16. AMS technically Programmed in Delphi (Pascal) Contributions by others in form of DLL’s Access database (through ADO) Executable that does not require any other software Share database on network

17. Main Window

18. DEMO 1 The agromet database

19. SUIVI : Database for agromet data Daily, Dekadal and Monthly weather station (point) data Every operation through flexible stationlist Add parameters easily Flexible ASCII import

20. Database technically Database in Microsoft ACCESS 2000 format Accessible from outside AMS Very common database format Query generator in Access Database can be placed on network Exchange of data with large database (Oracle SQL Server etc.) Early versions had Paradox tables

21. Demo Inventory Lists and base list Parameters Data entry View data on map, graph, report Formulas and calculation Aggregation Import from image and ASCII file

22. DEMO 2 Calculating a Water Balance

23. Water Balance Model based on the work of Frere/Popov and Rene Gommes Improvements so far: Irrigation (amount at planting or dekad by dekad) Phenological stages : initial, vegetative, flowering, ripening Crop coefficients based on 9 rather than 4 graph points Daily Time Steps More sets of crop coefficients per crop “Run file” approach

24. Water Balance (2) AMS does not operate directly on database, but on ASCII files. ASCII files are first exported from the database Two possibilities: 1.Monitoring (1 year; many stations) 2.Risk Analysis (1 stations; many years)

25. DEMO Close look at crops Dekadal and daily time steps With and without irrigation View results Make images from results Automation

26. DEMO 3 Integrating and analyzing data

27. Data integration (1) Technically data come as: Points Areas Images (or grids) Images are best for analysis Very visual (easy to check results) A picture tells more than a 1000 words Easy arithmetic with pixels

28. Demo Integrate Water Balance results with Yield data WB results : point data Yields : From ministry (area aggregated) Turn both into images Study the relation between Yield and Water Satisfaction Index geographically