The devastating crop losses caused by the drought in Malawi in 2015-2016, was initially not considered to be a major problem as the government had purchased insurance and was prepared for such calamity. However, the insurer’s model failed to estimate the scale of damage causing a delay in payments to millions of farmers. Prompt payments would have greatly reduced the effects of the damage that spread across the country. As a way to solve these problems, improvement of agricultural index insurance using crop models and remote sensing technology, which have made remarkable progress in recent years, has been proposed. 

In January 2021, a team of economists and earth system scientists published a review paper in Natural Reviews Earth & Environment discussing the potential of integrating remote sensing, crop modeling and economics in agricultural risk management. The authors make the following recommendations to improve the quality, reliability, affordability and accessibility of index insurance:
1. Exploring the full potential of higher-resolution spatial data and new data products on environmental conditions.
2. Improving loss detection with better crop modeling, new data products enabled by remote sensing, and use of additional data sources such as drones and smartphones.
3. Using better on-the-ground data that will help bolster the usefulness and quality of insurance programs.
4. Optimizing insurance zones to better reflect the geographic, microclimatic, and crop-management conditions that influence the productivity of specific landscapes.
5. Designing contracts to accommodate a variety of needs and the inevitability of index failure.

With the support of the International Rice Research Institute (IRRI) and the Japanese government, JIRCAS is jointly developing WeRise (Weather-rice-nutrient integrated decision support system) for rain-fed rice farmers using seasonal forecasts. WeRise is a tool that combines seasonal forecasts with crop growth models to predict the optimal time for sowing, transplanting and fertilization according to the cultivation area and rice variety, and to improve the adaptability of rainfed rice farmers to climate change. This collaborative research project of JIRCAS with IRRI and PhilRice also includes construction of database on rice growth and weather, field trials in the local rainfed farms, and training of agricultural extension workers in using WeRise on site.

In addition, in developing areas where it is difficult to mitigate disasters caused by extreme phenomena through civil engineering measures, the JIRCAS Project on Climate Change Measures in Agricultural Systems is also considering adaptation measures such as crop weather index insurance that protects farm management from such disasters, in addition to investigating the implications of adaptation measures in mitigating damage due to natural disasters. 
 

References

Elinor Benami et al. Uniting remote sensing, crop modeling and economics for agricultural risk management, Nature Reviews Earth & Environment (2021). DOI: 10.1038/s43017-020-00122-y

Advances in modeling and sensors can help farmers and insurers manage risk. January 21, 2021. https://phys.org/news/2021-01-advances-sensors-farmers.html

Contributors: HAYASHI Keiichi, OGAWA Satoshi (Crop, Livestock and Environment Division)