In her dissertation, Rahel focused on how statistical crop modelling can support climate risk management in tropical agriculture. Therefore, she further developed a statistical crop model focusing on robust validation, a better representation of weather extremes, and improving the transferability to other regions. Based on the model, she provided a robust maize yield forecast 6 weeks before the harvest in Tanzania and a food availability forecast in Burkina Faso.
The thesis includes 3 publications:
Laudien, Schauberger, Makowski, Gornott, 2020: Robustly forecasting maize yields in Tanzania based on climatic predictors, Nature Scientific Reports, Volume 10. https://www.nature.com/articles/s41598-020-76315-8
Laudien, Schauberger, Waid, Gornott, 2022: A forecast of staple crop production in Burkina Faso to enable early warnings of shortages in domestic food availability, Nature Scientific Reports, Volume 12. https://www.nature.com/articles/s41598-022-05561-9
Laudien, Schauberger, Gleixner, Gornott, 2020: Assessment of weather-yield relations of starchy maize at different scales in Peru to support the NDC implementation, Agricultural and Forest Meteorology, Volume 295. https://www.sciencedirect.com/science/article/pii/S0168192320302562
