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

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

Objectives to research methodologies required to produce crop yield forecasts for small-scale/subsistence agriculture in South Africa 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 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 assess the potential to apply the crop yield forecasts to improve crop management decisions to make recommendations on future research and operational needs to make recommendations on future research and operational needs

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.

Study Area

Mean Annual Precipitation

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

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)

Seasonal Rainfall Forecast Regions

Seasonal Rainfall Forecasts

Rainfall Forecast Skill

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

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

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

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

Crop Management Strategies Simulated

Planting Dates Considered

Strategy Selection Methods

Forecast selected strategy varied while the long term strategy was fixed over the seasons forecasted 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 Benefit: Forecast selected strategy performs better than long term strategy

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

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

Frequency with which different crop management strategies performed better (1981/ /93)

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

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

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 incorporate current 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.

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……

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

Potential Forecast Applications Production, dissemination and uptake of crop yield forecasts is likely to be most successful for the first category of forecast application 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 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. 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.

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. 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. 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.