Application of seasonal climate forecasts to predict regional scale crop yields in South Africa

1. Application of seasonal climate forecasts to predict regional scale crop yields in South Africa Trevor Lumsden and Roland Schulze School of Bioresources Engineering and Environmental Hydrology University of KwaZulu-Natal, South Africa

2. Acknowledgements • START, IRI and the Packard Foundation – training institute and project funding • Dr Emma Archer – project mentor • University of KwaZulu-Natal – in kind support

3. Objectives • to research methodologies required to produce crop yield forecasts for small-scale/subsistence agriculture in South Africa • to evaluate the quality (accuracy) of crop yield forecasts produced • to assess the potential to apply the crop yield forecasts to improve crop management decisions • to make recommendations on future research and operational needs

4. Desktop crop simulation study focussing on assessing the potential to apply climate forecasts in small-scale/subsistence agriculture. Chose to focus on maize, this being the country’s staple crop.

5. Study Area

6. Mean Annual Precipitation

7. Methodolgy: Climate Forecast Selection • Several sources of climate forecasts considered for use in the study – local and international • Potentially limiting factors: • lead time (seasonal) • number of seasons archived (for testing) • availability of corresponding obseved data for downscaling

8. Methodolgy: Climate Forecast Selection Most suitable forecasts: A set of historical rainfall forecasts (hindcasts) produced by the South African Weather Service (SAWS) for validation of their statistical seasonal rainfall forecast model (Landman and Klopper, 1998)

9. Seasonal Rainfall Forecast Regions

10. Seasonal Rainfall Forecasts

11. Rainfall Forecast Skill

12. Methodology: Downscaling Climate Forecasts • Spatial domain: Forecast region → Quaternary Catchment (QC) • Temporal domain: Categorical 4 month rainfall → daily values • Different methods considered • Selected use of historical analogues • simple and robust method • data required was available

13. Methodology: Downscaling Climate Forecasts • Analogues drawn from 1950/51 – 1979/80 • Therefore 10 analogues per tercile • Method results in multiple yield outcomes for a season • Date of forecast: 1 month prior to planting • Seasons for forecast evaluation: 1981/82 – 1992/93 • Climate files for crop model prepared using data from the relevant analogue seasons

14. Methodology: Crop Yield Simulation • Applied Ceres-Maize simulation model • Simulated 9 crop management strategies representing all combinations of 3 different planting dates and 3 different plant populations • Focussed on these variables as they are important climate sensitive decisions • Do forecasts improve strategy selection?

15. Crop Yield Simulation • Assumed manure fertilizers applied – typical application rate and nitrogen content • Assumed a single crop cultivar that is recommended throughout maize growing region. Parameters obtained from the Grain Crops Institute.

16. Crop Management Strategies Simulated

17. Planting Dates Considered

18. Strategy Selection Methods

19. Strategy Selection Methods • Forecast selected strategy varied while the long term strategy was fixed over the seasons forecasted • Benefit: Forecast selected strategy performs better than long term strategy

20. Simulating the performance of the forecast selected and long term strategies Having identified strategies according to the two methods, the performance of the strategies during the forecast seasons (1981/82 – 1992/93) was simulated using the observed records from those seasons

21. Usefulness of Yield Forecasts Assessed by comparing: forecast selected strategy yields vs long term strategy yields

22. Frequency with which different crop management strategies performed better (1981/82-1992/93)

23. Differences in yields obtained from forecast selected and long term strategies (cases where former outperformed latter)

24. Cases where Forecast Selected Strategies Outperformed Long Term Strategies on a Seasonal Basis: KwaZulu-Natal

25. Conclusions and Recommendations • Usefulness of the crop yield forecasts, varied across the catchments with the greatest forecast usefulness being in KwaZulu-Natal province. • The yield forecasting methodology should incorporatecurrent climate forecast formats (terciles with associated probabilities). • If there are an insufficient number of climate forecast seasons for evaluation purposes, additional climate forecasts should be generated retrospectively • Strategy selection should also consider risk minimization practices such as applying a variety of strategies in case a particular strategy fails. As confidence in yield forecasts grows, forecast selected strategies could be applied more extensively. • The application of crop yield forecast information in crop management decisions should be assessed in more detailed case studies where: • practical farming constraints can be taken into account • field data should be collected to ensure crop model inputs are realistic and to verify forecasts • forecasts could be more tailored to the livelihoods of farmers.

26. Conclusions and Recommendations Based on project experience (including a review of forecast information currently available) three potential applications of crop yield forecasts to small-scale/subsistence agriculture were identified for further research and implementation in the country……

27. Potential Yield Forecast Applications Identified for Small Scale Agriculture in South Africa

28. Potential Forecast Applications • Production, dissemination and uptake of crop yield forecasts is likely to be most successful for the first category of forecast application • The crop yield forecasts produced in this research would fit into the second category of forecast applications. These forecasts could be used as a source of quantitative information in current agricultural advisories disseminated to farmers via extension services. • The detailed case studies proposed previously would fit into the third category of forecast application. If the case studies prove successful, the sites studied could become demonstration sites showing the value of applying forecast information in decision-making.

29. Possible Future Projects • Detailed case studies: Apply medium to long term climate forecasts at ± 5 sites to manage crops. Compare with farmer managed fields. Consider strategies available/specific to farmer. Collect observed data. • Apply short to long term climate forecasts in 2-3 river basins, combined with near real time observed data, to forecast water resources and crop yields to aid in general water resources management and agricultural water management. Pilot study for national forecasting system.