For more information see ugamp.nerc.ac.uk/promise

1. PROMISEPredictability and variability of monsoons and the agricultural and hydrological impacts of climate change A 3 year research project funded under Framework 5 of the European Union (grant number EVK2-CT-1999-00022) For more information see http://ugamp.nerc.ac.uk/promise

2. Talk outline • Goals and structure of PROMISE • Examples of PROMISE research • International conference we are planning for 2003

3. World population prospects … Source: United Nations Population Division 1998  India predicted to be the most populated country by 2050

4. Bologna PROMISE Partners University of ReadingCIRADCNRMDMIICTPCEHLMDMPIThe Met OfficeECMWFCRCCINECAIITM

5. Goals of PROMISE PROMISE aims to improve understanding of: • The potential for seasonal prediction and the benefits that would accrue in terms of the management of water resources and agriculture • The impacts of climate change on tropical countries, in particular on the availability of water resources for human use and on the productivity of crops and the potential changes in natural vegetation

6. Links with end-users • Development of a data archive • Visits to CGIAR centres • ICTP workshop (held in 2001) • International conference to be held in 2003 • For more information see: • http://ugamp.nerc.ac.uk/promise/research/endusers

7. PROMISE Research and Support Assessment of anthropogenic climate changes for monsoon climates Impact of climate change on ground hydrology and agriculture Natural variability and predictability of current monsoon climates + Development of a database of observed and simulated data on meteorology, hydrology and agriculture Establishment of active links with climate scientists in monsoon affected countries

8. Main areas of PROMISE research ERA-40 Sensitivity of monsoon variability to sea surface temperatures Seasonal predictability and natural variability of monsoon climates DEMETER Hydrological and agricultural impacts of climate change in monsoon-affected countries Sensitivity of monsoon variability to land-surface processes Assessment of future monsoon climates Impact of land-use changes on future monsoon climates ERA-40

9. Integrated climate modelling

10. Examples of PROMISE research • Development of a hydrological model that can be integrated with regional climate models (GWAVA) • Development of a crop model that can be integrated with seasonal forecast to produce yield estimates in Senegal (GCH4) • Development of a large scale crop model that can be combined with GCMs to produce long term forecasts of yields that can be used for planning (HAPPY)

11. GWAVAGlobal Water AVailability AssessmentJeremy MeighCentre for Ecology & Hydrology(Institute of Hydrology)Wallingford, UKin conjunction withBritish Geological Survey

12. Overall objective • Develop a methodology for the assessment of water resources in relation to water demands which can be applied globally

13. GWAVA Detailed Objectives • Consistent methodology at the global scale • Representation of spatial variability in water availability and demands • Representation of seasonal and year-to-year variability in water resources • Accounting for the real properties of water resources systems • Tackling problems of international basins • Combined treatment of surface and groundwater • Ability to take into account scenarios of population growth, urbanisation, economic development and climate change

14. General approach • 0.5 by 0.5 degree grid for both water availability and demands • Linking grid cells to simulate river network • Models to account for effects of: • lakes, reservoirs and wetlands • abstractions and return flows • inter-basin transfers • Water demands based on current and projected population and livestock numbers, information on irrigation and industrial use • Indices of water availability versus demand derived at the grid cell scale

15. Inputs and data sources • Physical and water resources data • Elevation, River network • Vegetation, Soil type • Lakes, Reservoirs and Wetlands • Aquifer properties • Climate • Rainfall - 30 year time series, Evaporation • Demand related information • Population, Livestock numbers, Industrial and Irrigation demands

16. River network and cell linkages Red Sea Indian Ocean

17. Change in annual water demand, 2050

18. -2.00 to -1.90 -1.75 to -1.50 -1.00 to -0.50 -0.20 to 0.20 0.50 to 1.00 1.50 to 1.75 1.90 to 2.00 Change in water availability index • 2050, taking in to account: • Supply changes due to climatechange • Demand changes due to: • increasing population • population distribution • increasing per capita demands (improved living standards and industrialisation)

19. Application of model to West Africa River network Density of trees Soil type

20. Examples of PROMISE research • Development of a hydrological model that can be integrated with regional climate models (GWAVA) • Development of a crop model that can be integrated with seasonal forecast to produce yield estimates in Senegal (GCH4) • Development of a large scale crop model that can be combined with GCMs to produce long term forecasts of yields that can be used for planning (HAPPY)

21. DHC_CP Diagnostic Hydrique des Cultures Champs Pluviométriques Crop Water Balance Calculation Using Satellite based Rainfall Estimates Presented by : Abdallah SAMBA, Agrometeorologist AGRHYMET Regional Centre at Niamey, NIGER Trieste, June 2001 CIRAD AGRHYMET

22. Introduction • Need to forecast the yields of food crops in order to : • best manage the cereal stocks • control the distribution of food • start food aid in time • Using water balance simulation to obtain parameters which enable estimation of yields.

23. Water fluxes and their effects on agricultural hydrosystem ( ) ( ) Agricultural production Precipitation Soil evaporation Crop transpiration Runoff Erosion Drainage Capillary rise Lixiviation Ground water

24. Simplification for Water Balance simulation (The DHC4 model ) Agricultural production Precipitation Crop transpiration Soil evaporation Drainage Ground water

25. METEOSAT Satellite Agrometeorological Stations WATER BALANCE SIMULATION n years x stations • File • Screen • GIS • Spreadsheet • Printer n stations Rainfall data RESULTS Stochastic Rainfall Generation Parameter Calibration • DATA BASES • PET • Historical rainfall data CIRAD AGRHYMET

26. Examples of PROMISE research • Development of a hydrological model that can be integrated with regional climate models (GWAVA) • Development of a crop model that can be integrated with seasonal forecast to produce yield estimates in Senegal (GCH4) • Development of a large scale crop model that can be combined with GCMs to produce long term forecasts of yields that can be used for planning (HAPPY)

27. Combined weather/crop forecasting forgroundnut in India Andy Challinor, Tim Wheeler and Julia Slingo University of Reading

28. Weather  Farm - management - decisions   Crop Soil Genotype

29. Country + district field Spatial scale annual + seasonal monthly daily GCM Timescale Crop models

30. Country + district field Spatial scale annual + seasonal monthly daily Timescale  rainfall  groundnut

31. Country + district field Spatial scale annual + seasonal monthly daily Timescale  rainfall  groundnut Large area model

32. Huge Area Potential Peanut Yield (HAPPY!!) model

33. Calibrating and testing HAPPY • Calibrate using field/district data. • Test in hindcast mode using ERA-40 data to drive HAPPY. • Compare predicted crop yields with observed crop yields. • Re-calibrate HAPPY?

34. General Circulation Model weather forecast spatial parameters Crop model (HAPPY) Probabilistic outputs Crop model uncertainties Large area model crop forecast output processing

35. International PROMISE conference 24th – 28th March 2003 ICTP in Trieste currently sponsored by EU PROMISE, ICTP, WCRP, START/CLIMAG Monsoon environments: Agricultural and hydrological impacts of seasonal variability and climate change

36. Monsoon environments: Agricultural and hydrological impacts of seasonal variability and climate changeConference topics • The impacts of anthropogenic climate change on hydrology, agriculture and natural vegetation in monsoon-affected countries • Seasonal predictability of monsoon climates and the management of water resources and agriculture • Data provision for scientists from monsoon-affected countries using the PROMISE data archive as an example. • Use of seasonal forecasts as an operational tool • Applications of crop and hydrological model output to decision-making processes in developing countries • Future of integrated climate/impacts modelling

37. Monsoon environments: Agricultural and hydrological impacts of seasonal variability and climate changePlanned sessions • Seasonal predictability and natural variability of monsoon climates • Assessment of future monsoon climates in response to anthropogenic climate change • Sensitivity of monsoon variability to land-surface processes • Agricultural impacts of climate change • Hydrological impacts of climate change • Bringing together scientists and end users

38. Monsoon environments: Agricultural and hydrological impacts of seasonal variability and climate changeParticipants • PROMISE partners • Representatives from aid agencies • Climate scientists from developing countries • Policy makers / people involved with long term planning • European and American scientists working on PROMISE-related topics

39. Summary • PROMISE is an interdisciplinary project which aims to improve understanding of the impacts of climate change on monsoon environments • An international conference is planned for March 2003 which we hope will involve both researchers and end-users of research • FAO’s involvement in PROMISE and particularly the conference would provide an exciting opportunity for collaboration

40. Further information • Find out more about PROMISE: • web site: http://ugamp.nerc.ac.uk/promise • brochure – a few copies here also download from the web site • E-mail or phone me: emily@met.rdg.ac.uk +44 118 9316608 • attend the next annual PROMISE meeting in mid-May in Paris