Biophysical models and meta-modelling to reduce the basis risk in index-based insurance: A case study on winter cereals in Italy

Agricultural insurance is crucial for transferring a significant portion of the risk due to unfavourable weather conditions outside the farm. Index-based insurances were proposed as an alternative to traditional products based on direct damage assessment because of their potential to reduce insurance costs while being unaffected by subjectivity during damage quantification. However, they may be affected by basis risk when indices are poorly related with the underlying biological processes and thus with actual yield losses. To overcome this limitation, we developed a new framework to derive indices characterized by a low basis risk, based (i) on the use of a complex biophysical crop model extended to account for the extreme weather events of interest and (ii) on crop- and region-specific meta-models derived from the input-output structure of the crop model. The procedure was applied to frost and drought-heat damage to barley, soft and durum wheat in two Italian regions. Meta-models resulted easy to understand for farmers and accurate in reproducing percentage yield losses, with mean normalized relative root mean square error equal to 27.0% and 39.0% for damage caused respectively by frost and by the combined effect of drought and heat. The procedure, successfully adopted in operational contexts for the injuries and crops considered in this study, is going to be extended to other weather events, crops and regions.

Automated summary

Agricultural insurance is essential for transferring the risk caused by unfavorable weather conditions outside the farm. Index-based insurances, as an alternative to traditional products, have the potential to reduce costs but may be affected by basis risk when poorly related to underlying biological processes and actual yield losses.